Automatic control engineering Books

Book Synopsismlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with custom learners, measures, or pipeline components.Features: In-depth coverage of the mlr3 ecosystem for users and developers Explanation and illustration of basic and advanced machine learning concepts Ready to use code samples that can be adapted by the useTable of Contents1. Introduction and Overview. 2. Data and Basic Modeling. 3. Evaluation and Benchmarking. 4. Hyperparameter Optimization. 5. Advanced Tuning Methods and Black Box Optimization. 6. Feature Selection. 7. Sequential Pipelines. 8. Non-sequential Pipelines and Tuning. 9. Preprocessing. 10. Advanced Technical Aspects of mlr3 .11. Model Interpretation and Explanation. 12. Model Interpretation. 13. Beyond Regression and Classification. 14. Algorithmic Fairness.

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Deep Learning for Engineers introduces the fundamental principles of deep learning along with an explanation of the basic elements required for understanding and applying deep learning models.As a comprehensive guideline for applying deep learning models in practical settings, this book features an easy-to-understand coding structure using Python and PyTorch with an in-depth explanation of four typical deep learning case studies on image classification, object detection, semantic segmentation, and image captioning. The fundamentals of convolutional neural network (CNN) and recurrent neural network (RNN) architectures and their practical implementations in science and engineering are also discussed.This book includes exercise problems for all case studies focusing on various fine-tuning approaches in deep learning. Science and engineering students at both undergraduate and graduate levels, academic researchers, and industry professionals will find the contents

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Book SynopsisThe breadth of problems that can be solved with data science is astonishing, and this book provides the required tools and skills for a broad audience. The reader takes a journey into the forms, uses, and abuses of data and models, and learns how to critically examine each step. Python coding and data analysis skills are built from the ground up, with no prior coding experience assumed. The necessary background in computer science, mathematics, and statistics is provided in an approachable manner.Each step of the machine learning lifecycle is discussed, from business objective planning to monitoring a model in production. This end-to-end approach supplies the broad view necessary to sidestep many of the pitfalls that can sink a data science project. Detailed examples are provided from a wide range of applications and fields, from fraud detection in banking to breast cancer classification in healthcare. The reader will learn the techniques to accomplish tasks that include predicting outcomes, explaining observations, and detecting patterns. Improper use of data and models can introduce unwanted effects and dangers to society. A chapter on model risk provides a framework for comprehensively challenging a model and mitigating weaknesses. When data is collected, stored, and used, it may misrepresent reality and introduce bias. Strategies for addressing bias are discussed. From Concepts to Code: Introduction to Data Science leverages content developed by the author for a full-year data science course suitable for advanced high school or early undergraduate students. This course is freely available and it includes weekly lesson plans.

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Book SynopsisThe Applied Genomic Epidemiology Handbook: A Practical Guide to Leveraging Pathogen Genomic Data in Public Health provides rationale, theory, and implementation guidance to help public health practitioners incorporate pathogen genomic data analysis into their investigations. During the SARS-CoV-2 pandemic, viral whole genome sequences were generated, analyzed, and shared at an unprecedented scale. This wealth of data posed both tremendous opportunities and challenges; the data could be used to support varied parts of the public health response but could be hard for much of the public health workforce to analyze and interpret, given a historical lack of experience working with pathogen genomic data.This book addresses that gap. Structured into eight wide-ranging chapters, this book describes how the overlapping timescales of pathogen evolution and infection transmission enable exploration of epidemiologic dynamics from pathogen sequence data. Different approaches to s

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Book SynopsisThis groundbreaking book explores the power of collaborative AI in amplifying human creativity and expertise. Written by two seasoned experts in data analytics, AI, and machine learning, the book offers a comprehensive overview of the creative process behind AI-powered content generation. It takes the reader through a unique collaborative process between human authors and various AI-based topic experts, created, prompted, and fine-tuned by the authors.This book features a comprehensive list of prompts that readers can use to create their own ChatGPT-powered topic experts. By following these expertly crafted prompts, individuals and businesses alike can harness the power of AI, tailoring it to their specific needs and fostering a fruitful collaboration between humans and machines. With real-world use cases and deep insights into the foundations of generative AI, the book showcases how humans and machines can work together to achieve better business outcomes and tackle complex

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Book SynopsisMachine learning is a dynamic and rapidly expanding field focused on creating algorithms that empower computers to recognize patterns, make predictions and continually enhance performance. It enables computers to learn from data and experiences, making decisions without explicit programming. For learners, mastering the fundamentals of machine learning opens doors to a world of possibilities to build robust and accurate models. In the ever-evolving landscape of machine learning, datasets play a pivotal role in shaping its future. The field has been revolutionized with the introduction of oneAPI, which provides a unified programming model across different architectures, including CPUs, GPUs, FPGAs and accelerators, fostering an efficient and portable programming environment. Embracing this unified model empowers practitioners to build efficient and scalable machine learning solutions, marking a significant stride in cross-architecture development. Dive into this fascinating field to m

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Book SynopsisResponsible use of AI in public sector applications requires engagement with various technical and non-technical areas such as human rights, inclusion, diversity, innovation, and economic growth. The book covers topics spanning the technological socio-economic spectrum including potential of AI/ML technologies to address social and political inequities, privacy enhancing technologies for datasets, friction less data sharing and data stewardship models, regional/geographical inequities in extraction and so forth.Features: Focuses on technical aspects of responsible AI in the public sector. Covers a wide range of topics spanning the technological socio-economic spectrum. Presents viewpoints from the public sector agencies as well as from practitioners. Discusses privacy enhancing technologies for collecting, processing and storing datasets, and friction. Reviews frameworks to identify and address biased AI outcomes in the design, development and use of AI. This book is aimed at professionals, researchers and students in artificial intelligence, computer science and engineering, policy makers, social scientists, economists, and lawyers.

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Book SynopsisComputational methods are necessary for the proper execution of the applications for the benefit of society and technological development. Technological development makes life easier by constructing powerful systems with the help of computational methods. The nature of computational methods changes from time to time and retains only efficient applicable theories. Researchers take the idea of existing computational systems and advanced them as per the possible future needs. Efficient computational methods also solve complex problems and help to make the system more intelligent. Automation process requires decision-making computational systems. A more intelligent system contains an efficient computational method, which is described by powerful algorithm development. The aim of this book is to identify the technological development for future computational systems, which ultimately reflects the more intelligent system. Automation is the need of todayâs world, and the computational systems need to be upgraded to that level to perform the required tasks. The most efficient computational algorithm acts like a human being and offers a full sense of intelligent automation.This book: Presents the latest research trends for the upcoming computational intelligent systems in a comprehensive manner. Focuses on the integration of multi-purpose and multi-dimension natural language into intelligent systems. Elaborates on nature-inspired and intelligent behaviour-based computational methods to deal with the observation of nature. Illustrates applications of quantum cellular energy-efficient computing methods for automation and applications of genetic algorithms in multi-disciplinary fields. Discusses aspects of intelligent automation like technology-based, architecture-based, logic implementation-based, and the different algorithms-based concepts. It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

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Book SynopsisIs a computer simulation of a brain sufficient to make it intelligent? Do you need consciousness to have intelligence? Do you need to be alive to have consciousness? This book has a dual purpose. First, it provides a multi-disciplinary research survey across all branches of neuroscience and AI research that relate to this book's mission of bringing AI research closer to building a human-level AI (HLAI) system. It provides an encapsulation of key ideas and concepts, and provides all the references for the reader to delve deeper; much of the survey coverage is of recent pioneering research. Second, the final part of this book brings together key concepts from the survey and makes suggestions for building HLAI. This book provides accessible explanations of numerous key concepts from neuroscience and artificial intelligence research, including: The focus on visual processing and thinking and the possible role of brain lateralization toward visual thinking and intelligence.

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Book SynopsisAfter many years during which it languished in relative obscurity - in remote classrooms of computer science departments and in small prototype projects for tech companies - AI is now a searingly hot topic across the media. Yet much of the public discussion is so feverish that an understanding of the basic scientific and engineering elements of the field is easily lost, often resulting in exaggerated claims, as well as dangerously neglected threats.This concise and sober book presents a brief history of AI, explaining in clear language the central engineering innovations that have produced the current revolution, and distinguishing between imagined dangers and the very real problems that AI is creating. Spread across seven short and accessible chapters, the book explains the developments behind deep learning and the applications of deep neural networks (DNNs), addresses both the imagined and actual risks posed by the AI revolution, before outlining rational public policy on AI, covering topics like tech monopolies, disinformation, bias, hate speech, intellectual property rights, and inequality. Suitable for the general reader, Understanding the Artificial Intelligence Revolution: Between Catastrophe and Utopia is the ideal book for anyone seeking a clear and informed introduction to AI.

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Book SynopsisThis engineering textbook is designed to introduce advanced control systems for vehicles, including advanced automotive concepts and the next generation of vehicles for ITS. For each automotive control problem considered, the authors emphasise the physics and underlying principles behind the control system concept and design.Table of ContentsPreface; Part I. Introduction and Background: 1. Introduction; 2. Automotive control system design process; 3. Review of engine modeling; 4. Review of vehicle dynamics; 5. Human factors and driver modeling; Part II. Powertrain Control Systems: 6. Air-to-fuel ratio control; 7. Control of spark timing; 8. Idle speed control; 9. Transmission control; 10. Control of hybrid vehicles; 11. Modeling and control of fuel cells for vehicles; Part III. Vehicle Control Systems: 12. Cruise and headway control; 13. Antilock brake systems and traction control; 14. Vehicle stability control; 15. Four wheel steering; 16. Active suspensions; Part IV. Intelligent Transportation Systems (ITS): 17. Overview of ITS; 18. Preventing collisions; 19. Automated highway systems (AHS) and platooning; 20. Lateral active safety systems and automated steering; Appendix A. Review of control theory fundamentals; Appendix B. Two-mass three DOF vehicle lateral/yaw/roll model.

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Book SynopsisThis mathematically rigorous guide to convex optimization for power systems engineering includes convex models for a variety of real-world applications, and a selection of problems and practical examples. An invaluable resource for students and researchers from industry and academia in power systems, optimization, and control.Table of Contents1. Introduction; 2. Background; 3. Optimal power flow; 4. System operation; 5. Infrastructure planning; 6. Economics; 7. Future directions.

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Book SynopsisDesign optimization is a standard concept in engineering design, and in other disciplines which utilize mathematical decision-making methods. This textbook focuses on the close relationship between a design problem's mathematical model and the solution-driven methods which optimize it. Along with extensive material on modeling problems, this book also features useful techniques for checking whether a model is suitable for computational treatment. Throughout, key concepts are discussed in the context of why and when a particular algorithm may be successful, and a large number of examples demonstrate the theory or method right after it is presented. This book also contains step-by-step instructions for executing a design optimization project - from building the problem statement to interpreting the computer results. All chapters contain exercises from which instructors can easily build quizzes, and a chapter on 'principles and practice' offers the reader tips and guidance based on the auTrade Review'Principles of Optimal Design, third edition, offers an excellent combination of depth and breadth of fundamentals of mathematical modeling of systems design. Students and practitioners will find the textbook a great starting point to learn about the systems design methods and optimization theories from the fundamentals to the advanced numerical methods. The recent addition of the decomposition-based optimization method and analytical target cascading is a nice expansion to the traditional optimization methods. I use this textbook to teach graduate and advanced undergraduate students who have basic understanding of numerical analysis. Students appreciate the spectrum of contents and they become ready to apply what they learn from the textbook to complex systems design cases. I highly recommend the textbook.' Harrison Hyung, University of Illinois, Urbana-Champaign'Principles of Optimal Design has always been a well-structured textbook that introduces students to the fundamentals of optimal design while remaining accessible and enjoyable to read. The latest edition adds many brief but exciting glimpses of more advanced topics in optimization. These additions have transformed the book from a 'foundation' on which students can firmly stand to a 'catapult' that can propel them to exciting, new, and advanced topics in the broad discipline of optimal design.' Hosam Fathy, Penn State College of Engineering'This third edition brings to the reader an impressive array of new and useful topics in optimal design. For example, and among others, new chapters on non-gradient based methods and decomposition-based optimization (or multi-disciplinary optimization, MDO) have been added. The book can be used both as a textbook for a graduate level course in all engineering fields, but also as a must have reference material. I highly recommend it!' Shapour Azarm, University of Maryland'The Principles of Optimal Design, third edition, is an excellent first text for undergraduates and graduate students alike interested in gaining a firm grasp of practical design optimization methods. It blends the latest modeling techniques with a rigorous treatment of the mathematical analysis, allowing one to adeptly navigate the varied landscapes of modern design problems. From machine learning, automotive systems, financial portfolios, to even the modeling of human purchasing behavior, I have used this text to teach my students how to systematically apply the design process to a broad range of engineering problems.' George J. Delagrammatikas, The Cooper Union for the Advancement of Science and Art, New York'This book, almost thirty years after its first edition, remains the only comprehensive text on engineering design optimization. In our 'one-click' software era, it provides theory fundamentals that tend to be neglected, while complementing them with rigorous modeling and computation techniques. I cannot think of a better textbook for engineering optimization courses, including a plethora of excellent examples and exercises. The third edition is enhanced with new and extremely useful material on recent developments in derivative-free optimization and optimal system design.' Michael Kokkolaras, McGill University, Canada'I've found Principles of Optimal Design to be an excellent, comprehensive explanation of design optimization methods, grounded in rigorous mathematics, yet still accessible. The addition of a gradient-free optimization chapter is a welcome addition to the book.' John Whitefoot, University of Pittsburgh'I've recommended this book to several students. It's a great resource for students who need to use optimization for practical purposes, such as a senior project or an assignment at their co-op job. The book has a good balance between the underlying theory and the application of that theory to actual problems.' Diane Peters, University of MichiganTable of ContentsPreface; Notation; 1. Optimization models; 2. Model construction; 3. Model boundedness; 4. Interior optima; 5. Boundary optima; 6. Local computation; 7. Nongradient search; 8. Systems design; 9. Principles and practice; Notes; References; Author index; Subject index.

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Book SynopsisIn this comprehensive textbook about robot grasping, readers will discover an integrated look at the major concepts and technical results in robot grasp mechanics. A large body of prior research, including key theories, graphical techniques, and insights on robot hand designs, is organized into a systematic review, using common notation and a common analytical framework. With introductory and advanced chapters that support senior undergraduate and graduate level robotics courses, this book provides a full introduction to robot grasping principles that are needed to model and analyze multi-finger robot grasps, and serves as a valuable reference for robotics students, researchers, and practicing robot engineers. Each chapter contains many worked-out examples, exercises with full solutions, and figures that highlight new concepts and help the reader master the use of the theories and equations presented.Trade Review'The Mechanics of Robot Grasping, by two of the world's leading experts, fills an important gap in the literature by providing the first comprehensive survey of the mathematical tools needed to model the physics of grasping. The book uses configuration space to consistently characterize equilibrium, immobilizing, and caging grasps, and clearly conveys important points such as the distinction between first-order and second-order form closure. The book also contains new material on the effects of gravity, compliance, and hand mechanism design. Grasping remains a Grand Challenge for robots and this book provides the solid foundation for progress for students and researchers in the years ahead.' Ken Goldberg, University of California, Berkeley'This is a book on robotic hand grasping from new view points. Different from other books on grasping, this book concretely explains the equilibrium grasp, the immobilizing grasp and the caging grasp. In addition, I have never seen a book discussing the equilibrium stance of legged robots in relation to the equilibrium grasp. Classical topics on grasping mechanics are also covered in this book.' Kensuke Harada, Osaka University, JapanTable of Contents1. Introduction and overview; Part I. Basic Geometry of the Grasping Process: 2. Rigid-body configuration space; 3. Configuration space tangent and cotangent vectors; 4. Rigid body equilibrium grasps; 5. A catalog of equilibrium grasps; Part II. Frictionless Rigid Body Grasps and Stances: 6. Introduction to secure grasps; 7. First-order immobilizing grasps; 8. Second-order immobilizing grasps; 9. Minimal immobilizing grasps; 10. Multi-finger caging grasps; 11. Frictionless hand supported stances under gravity; Part III. Frictional Rigid-Body Grasps, Fixtures, and Stances: 12. Wrench resistant grasps; 13. Grasp quality functions; 14. Hand supported stances under gravity – Part I; 15. Hand supported stances under gravity – Part II; Part IV. Grasping Mechanisms: 16. The kinematics and mechanics of grasping mechanisms; 17. Grasp manipulability; 18. Hand mechanism compliance; Appendices; Index.

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Book SynopsisThis book addresses the reader to use synergistically the concepts of membranes and sensors materials. It contains insightful contributions from leading scientists working in both the fields. The focus is on the fabrication of smart membranes from sensor materials and related impact on many technologically sophisticated areas such as telemedicine, microfluidics, drug delivery targeting, (bio)separation, labs-on-a-chip, textiles, power storage and release, environment monitoring, agro-food safety, cosmetics, architecture, automotive and so on. This book covers various topics, including the choice of materials and techniques for assembling responsive membranes with ability to transport mass, energy and signals on demand; the reader will find through the book an extensive description of the best techniques used to monitor molecular scale events, which are regarded as responsible for the smartness of multifunctional objects and for the conversion of chemical signals into optical,Table of ContentsPreface Part 1: Sensing Materials for Smart Membranes 1 1 Interfaces Based on Carbon Nanotubes, Ionic Liquids and Polymer Matrices for Sensing and Membrane Separation Applications 3 María Belén Serrano-Santos, Ana Corres Ortega, and Thomas Schäfer 1.1 Introduction 3 1.2 Ionic Liquid-Carbon Nanotubes Composites for Sensing Interfaces 5 1.3 Ionic Liquid Interfaces for Detection and Separation of Gases and Solvents 11 1.4 Ionic Liquid-Polymer Interfaces for Membrane Separation Processes 16 1.5 Conclusions 18 Acknowledgement 19 References 19 2 Photo-Responsive Hydrogels for Adaptive Membranes 21 David Díaz Díaz and Jeremiah A. Johnson 2.1 Introduction 21 2.2 Photo-Responsive Hydrogel Membranes 23 2.3 Photo-Thermally Responsive Hydrogel Membranes 44 2.4 Summary 46 2.5 Acknowledgements 48 Abbreviations 48 References 49 3 Smart Vesicles: Synthesis, Characterization and Applications 53 Jung-Keun Kim, Chang-Soo Lee, and Eunji Lee 3.1 Introduction 53 3.2 Synthesis of Soft Vesicles 54 3.3 Synthesis of Hard Vesicles 64 3.4 Characterization of Vesicular Structures 68 3.5 Stimuli-Responsive Behaviors of Vesicular Structures 72 3.6 Application of Vesicles 78 3.7 Conclusions 91 Acknowledgment 92 References 92 Part 2: Stimuli-Responsive Interfaces 105 4 Computational Modeling of Sensing Membranes and Supramolecular Interactions 107 Giacomo Saielli 4.1 Introduction 107 4.2 Non-covalent Interactions: A Physical and a Chemical View 109 4.3 Physical Interactions 109 4.4 Chemical Interactions 114 4.5 Computational Methods for Supramolecular Interactions 117 4.6 Classical Force Fields 127 4.7 Conclusions 139 References 140 5 Sensing Techniques Involving Thin Films for Studying Biomolecular Interactions and Membrane Fouling Phenomena 145 Gabriela Diaconu and Thomas Schäfer 5.1 Introduction 145 5.2 Quartz Crystal Microbalance with Dissipation Monitoring (QCM-D) 146 5.3 Surface Plasmon Resonance (SPR) 148 5.4 Applications of SPR and QCM-D 151 5.5 Conclusions 159 Acknowledgements 160 References 160 6 Smart Membrane Surfaces: Wettability Amplification and Self-Healing 161 Annarosa Gugliuzza 6.1 Introduction 161 6.2 Basics of surface wettability 162 6.3 Amplified Wettability 164 6.4 Actuation Mechanisms 165 6.5 Self-Powered Liquid Motion 170 6.6 Self-Cleaning Mechanisms 172 6.7 Self-Healing Concepts And Strategies 175 6.8 Repairable Surface Properties 177 6.9 Conclusions and Perspectives 179 References 180 7 Model Bio-Membranes Investigated by AFM and AFS: A Suitable Tool to Unravel Lipid Organization and their Interaction with Proteins 185 Andrea Alessandrini and Paolo Facci 7.1 Introduction 186 7.2 Supported Lipid Bilayers 189 7.3 Atomic Force Microscopy (AFM) and Phase Behavior of Slbs 199 7.4 Atomic Force Spectroscopy (AFS) of Supported Lipid Bilayers 205 7.5 Lipid/Protein Interactions 213 7.6 Conclusions 218 References 218 Part 3: Directed Molecular Separation 227 8 Self-Assembled Nanoporous Membranes for Controlled Drug Release and Bioseparation 229 Dominique Scalarone, Pierangiola Bracco, and Francesco Trotta 8.1 Introduction 229 8.2 General Aspects of Block Copolymer Self-Assembly 231 8.3 Block Copolymer Based Membranes 233 8.4 Fabrication of Nanoporous Membranes Derived from Block Copolymers 234 8.5 Tunability of Surface Properties 242 8.6 Application of Block Copolymer Derived Membranes to Bioseparation and Controlled Drug Release 244 8.7 Conclusion 250 References 250 Abbreviations 253 9 Hybrid Mesoporous Silica for Drug Targeting 255 Luigi Pasqua, Piluso Rosangela, Ilenia Pelaggi, and Catia Morelli 9.1 Introduction 256 9.2 Synthesis and Characterization of Bifunctional Hybrid Mesoporous Silica Nanoparticles Potentially Useful for Drug Targeting 257 9.3 Drug-Loaded Folic-Acid-Grafted Msns Specifically Target FR Expressing Tumour Cells [16] 260 9.4 Conclusion 266 References 268 10 Molecular Recognition-driven Membrane Processes 269 Laura Donato, Rosalinda Mazzei, Catia Algieri, Emma Piacentini, Teresa Poerio, and Lidietta Giorno 10.1 Molecular Imprinting Technique 270 10.2 Affinity Membranes 275 10.3 Cyclodextrins As Molecular Recognition Elements 281 10.4 Zeolite Membranes as Molecular Recognition Devices: Preparation and Characterization 283 10.5 Functionalized Particles-loaded Membranes For Selective Separation Based On Molecular Recognition 287 10.6 Biphasic Enzyme Membrane Systems with Enantioselective Recognition Properties ror Kinetic Resolution 291 10.7 Membrane Surface Modification 292 References 296 Part 4: Membrane Sensors and Challenged Applications 301 11 Electrospun Membranes for Sensors Applications 303 Pierangiola Bracco, Dominique Scalarone, and Francesco Trotta 11.1 Introduction 303 11.2 Basic Principles of Electrospinning 304 11.3 Control of the Electrospinning Process 306 11.4 Application of Electrospun Materials to Ultrasensitive Sensors 311 11.5 Conclusions 329 Abbreviations 330 References 330 12 Smart Sensing Scaffolds 337 Carmelo De Maria, Yudan Whulanza, Giovanni Vozzi, and Arti Ahluwalia 12.1 Introduction 337 12.2 Composite Sensing Biomaterial Preparation 339 12.3 Composite Sensing Biomaterial Characterisation 340 12.4 SWNTs-Based Composite Films Structural Properties 341 12.5 Tensile Properties of SWNTs-Based Composite Films 343 12.6 Electrical Properties of SWNTs-Based Composites Films 348 12.7 Electromechanical Characterisation and Strain-Dependence Measurement 350 12.8 Cell Sensing Scaffolds 352 12.9 Processing of CNT Composite: Microfabrication of Sensing Scaffold 360 12.10 Conclusions 361 References 362 13 Nanostructured Sensing Emulsion Droplets and Particles: Properties and Formulation by Membrane Emulsification 367 Emma Piacentini, Alessandra Imbrogno, and Lidietta Giorno 13.1 Introduction 367 13.2 Emulsions and Emulsification Methods 370 13.3 Senging Particles Produced by Membrane-Based Process 389 13.4 Conclusions 397 References 398 14 Membranes for Ultra-Smart Textiles 401 Annarosa Gugliuzza and Enrico Drioli 14.1 Introduction 401 14.2 Membranes and Comfort 403 14.3 Adaptive Membranes for Smart Textiles 407 14.4 Barrier Functions of Membranes 411 14.5 Membrane Materials for Self-cleaning Function 413 14.6 Interactive Membranes for Wearable Electronics 414 14.7 Conclusions and Prospects 415 References 416

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Book SynopsisFoundations of Fuzzy Control: A Practical Approach, 2nd Edition has been significantly revised and updated, with two new chapters on Gain Scheduling Control and Neurofuzzy Modelling. It focuses on the PID (Proportional, Integral, Derivative) type controller which is the most widely used in industry and systematically analyses several fuzzy PID control systems and adaptive control mechanisms. This new edition covers the basics of fuzzy control and builds a solid foundation for the design of fuzzy controllers, by creating links to established linear and nonlinear control theory. Advanced topics are also introduced and in particular, common sense geometry is emphasised. Key features Sets out practical worked through problems, examples and case studies to illustrate each type of control system Accompanied by a website hosting downloadable MATLAB programs Accompanied by an online course on Fuzzy Control which is taught by the author. StTable of ContentsForeword xiii Preface to the Second Edition xv Preface to the First Edition xvii 1Introduction 1 1.1 What Is Fuzzy Control? 1 1.2 Why Fuzzy Control? 2 1.3 Controller Design 3 1.4 Introductory Example: Stopping a Car 3 1.5 Nonlinear Control Systems 9 1.6 Summary 11 1.7 The Autopilot Simulator* 12 1.8 Notes and References* 13 2 Fuzzy Reasoning 17 2.1 Fuzzy Sets 17 2.2 Fuzzy Set Operations 25 2.3 Fuzzy If–Then Rules 33 2.4 Fuzzy Logic 36 2.5 Summary 43 2.6 Theoretical Fuzzy Logic* 43 2.7 Notes and References* 53 3 Fuzzy Control 55 3.1 The Rule Based Controller 56 3.2 The Sugeno Controller 61 3.3 Autopilot Example: Four Rules 64 3.4 Table Based Controller 65 3.5 Linear Fuzzy Controller 68 3.6 Summary 70 3.7 Other Controller Components* 70 3.8 Other Rule Based Controllers* 77 3.9 Analytical Simplification of the Inference* 80 3.10 Notes and References* 84 4 Linear Fuzzy PID Control 85 4.1 Fuzzy P Controller 87 4.2 Fuzzy PD Controller 89 4.3 Fuzzy PD+I Controller 90 4.4 Fuzzy Incremental Controller 92 4.5 Tuning 94 4.6 Simulation Example: Third-Order Process 99 4.7 Autopilot Example: Stable Equilibrium 101 4.8 Summary 103 4.9 Derivative Spikes and Integrator Windup* 104 4.10 PID Loop Shaping* 106 4.11 Notes and References* 109 5 Nonlinear Fuzzy PID Control 111 5.1 Nonlinear Components 111 5.2 Phase Plot 113 5.3 Four Standard Control Surfaces 115 5.4 Fine-Tuning 118 5.5 Example: Unstable Frictionless Vehicle 121 5.6 Example: Nonlinear Valve Compensator 124 5.7 Example: Motor Actuator with Limits 127 5.8 Autopilot Example: Regulating a Mass Load 127 5.9 Summary 130 5.10 Phase Plane Analysis* 130 5.11 Geometric Interpretation of the PD Controller* 134 5.12 Notes and References* 143 6 The Self-Organizing Controller 145 6.1 Model Reference Adaptive Systems 145 6.2 The Original SOC 147 6.3 A Modified SOC 150 6.4 Example with a Long Deadtime 151 6.5 Tuning and Time Lock 155 6.6 Summary 157 6.7 Example: Adaptive Control of a First-Order Process* 157 6.8 Analytical Derivation of the SOC Adaptation Law* 161 6.9 Notes and References* 169 7 Performance and Relative Stability 171 7.1 Reference Model 172 7.2 Performance Measures 177 7.3 PID Tuning from Performance Specifications 180 7.4 Gain Margin and Delay Margin 185 7.5 Test of Four Difficult Processes 186 7.6 The Nyquist Criterion for Stability 188 7.7 Relative Stability of the Standard Control Surfaces 191 7.8 Summary 193 7.9 Describing Functions* 193 7.10 Frequency Responses of the FPD and FPD+I Controllers* 198 7.11 Analytical Derivation of Describing Functions for the Standard Surfaces* 206 7.12 Notes and References* 216 8 Fuzzy Gain Scheduling Control 217 8.1 Point Designs and Interpolation 218 8.2 Fuzzy Gain Scheduling 219 8.3 Fuzzy Compensator Design 221 8.4 Autopilot Example: Stopping on a Hilltop 226 8.5 Summary 228 8.6 Case Study: the FLS Controller* 229 8.7 Notes and References* 235 9 Fuzzy Models 237 9.1 Basis Function Architecture 238 9.2 Handmade Models 240 9.3 Machine-Made Models 249 9.4 Cluster Analysis 253 9.5 Training and Testing 263 9.6 Summary 266 9.7 Neuro-Fuzzy Models* 267 9.8 Notes and References* 275 10 Demonstration Examples 277 10.1 Hot Water Heater 277 10.2 Temperature Control of a Tank Reactor 282 10.3 Idle Speed Control of a Car Engine 287 10.4 Balancing a Ball on a Cart 292 10.5 Dynamic Model of a First-Order Process with a Nonlinearity 301 10.6 Summary 307 10.7 Further State-Space Analysis of the Cart-Ball System* 307 10.8 Notes and References* 314 References 315 Index 319

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Book SynopsisWidely used across industrial and manufacturing automation, Programmable Logic Controllers (PLCs) perform a broad range of electromechanical tasks with multiple input and output arrangements, designed specifically to cope in severe environmental conditions such as automotive and chemical plants. Programmable Logic Controllers: A Practical Approach using CoDeSys is a hands-on guide to rapidly gain proficiency in the development and operation of PLCs based on the IEC 61131-3 standard. Using the freely-available* software tool CoDeSys, which is widely used in industrial design automation projects, the author takes a highly practical approach to PLC design using real-world examples. The design tool, CoDeSys, also features a built in simulator/soft PLC enabling the reader to undertake exercises and test the examples. Key features: Introduces to programming techniques using IEC 61131-3 guidelines in the five PLC-recognised programming languages. FocusesTable of ContentsPreface xiv Part One Hardware 1 1 About PLCs 3 1.1 History 4 1.1.1 More Recent Developments 6 1.2 Structure 7 1.2.1 Inputs and Outputs 10 1.3 PLC Operation 13 1.3.1 Process Knowledge 14 1.3.2 Standard Operations 16 1.3.3 Cyclic, Freewheeling, or Event‐Controlled Execution 18 1.4 Test Problems 19 2 Digital Signals and Digital Inputs and Outputs 20 2.1 Introduction 20 2.2 Terminology 21 2.2.1 Discrete, Digital, Logical, and Binary 21 2.2.2 Sensors, Transducers, and Transmitters 22 2.3 Switches 24 2.3.1 Limit Switches 24 2.3.2 Safety Devices 24 2.3.3 Magnetic Switches 25 2.4 Logical Sensors 26 2.4.1 Inductive Sensors 27 2.4.2 Capacitive Sensors 29 2.4.3 Photocells 30 2.4.4 Ultrasonic Sensors 33 2.4.5 Rotating Sensors (Encoders) 34 2.4.6 Other Detection Principles and Sensors 37 2.5 Connection of Logical Sensors 39 2.5.1 Sink/Source 41 2.5.2 Selecting a Sensor with the Proper Type of Output 43 2.6 Properties of Discrete Inputs 44 2.7 Discrete Actuators 45 2.7.1 Relays and Contactors 46 2.7.2 Solenoids and Magnetic Valves 47 2.7.3 Transistor Outputs versus Relay Outputs 49 2.8 Test Problems 50 3 Analog Signals and Analog I/O 52 3.1 Introduction 52 3.2 Digitalization of Analog Signals 53 3.2.1 Filtering 53 3.2.2 A/D Conversion 55 3.3 Analog Instrumentation 58 3.3.1 About Sensors 58 3.3.2 Standard Signal Formats 59 3.3.3 On the 4–20 mA Standard 59 3.3.4 Some Other Properties of Sensors 61 3.4 Temperature Sensors 61 3.4.1 Thermocouple 61 3.4.2 PT100/NI1000 62 3.4.3 Thermistors 64 3.5 Connection 64 3.5.1 About Noise, Loss, and Cabling 64 3.5.2 Connecting Sensors 67 3.5.3 Connection of a PT100 (RTD) 68 3.5.4 Connecting Thermocouples 72 3.6 Properties of Analog Input Modules 72 3.6.1 Measurement Ranges and Digitizing: Resolution 72 3.6.2 Important Properties and Parameters 74 3.7 Analog Output Modules and Standard Signal Formats 75 3.8 Test Problems 76 Part Two Methodic 79 4 Structured Design 81 4.1 Introduction 81 4.2 Number Systems 82 4.2.1 The Decimal Number Systems 82 4.2.2 The Binary Number System 82 4.2.3 The Hexadecimal Number System 83 4.2.4 Binary‐Coded Decimal Numbers 85 4.2.5 Conversion between Number Systems 86 4.3 Digital Logic 87 4.4 Boolean Design 91 4.4.1 Logical Functional Expressions 91 4.4.2 Boolean Algebra 93 4.5 Sequential Design 97 4.5.1 Flowchart 97 4.5.2 Example: Flowchart for Mixing Process 99 4.5.3 Example: Flowchart for an Automated Packaging Line 101 4.5.4 Sequence Diagrams 107 4.5.5 Example: Sequence Diagram for the Mixing Process 110 4.5.6 Example: Batch Process 112 4.6 State‐Based Design 113 4.6.1 Why Use State Diagrams? 114 4.6.2 State Diagrams 114 4.6.3 Example: Batch Process 117 4.6.4 Example: Level Process 118 4.6.5 Example: Packing Facility for Apples 121 4.7 Summary 124 4.8 Test Problems 125 Part Three IEC 61131‐3 131 5 Introduction to Programming and IEC 61131‐3 133 5.1 Introduction 133 5.1.1 Weaknesses in Traditional PLCs 134 5.1.2 Improvements with IEC 61131‐3 136 5.1.3 On Implementation of the Standard 137 5.2 Brief Presentation of the Languages 138 5.2.1 ST 138 5.2.2 FBD 138 5.2.3 LD 139 5.2.4 IL 139 5.2.5 SFC 141 5.3 Program Structure in IEC 61131‐3 141 5.3.1 Example of a Configuration 145 5.4 Program Processing 146 5.4.1 Development of Programming Languages 146 5.4.2 From Source Code to Machine Code 147 5.5 Test Problems 151 6 IEC 61131‐3: Common Language Elements 152 6.1 Introduction 152 6.2 Identifiers, Keywords, and Comments 153 6.2.1 Identifiers 153 6.2.2 Keywords 154 6.2.3 Comments 154 6.3 About Variables and Data Types 156 6.4 Pragmas and Literals 156 6.4.1 Literal 157 6.5 Data Types 158 6.5.1 Numerical and Binary Data Types 158 6.5.2 Data Types for Time and Duration 161 6.5.3 Text Strings 163 6.5.4 Generic Data Types 164 6.5.5 User‐Defined Data Types 166 6.6 Variables 169 6.6.1 Conventional Addressing 170 6.6.2 Declaration of Variables with IEC 61131‐3 171 6.6.3 Local Versus Global Variables 174 6.6.4 Input and Output Variables 175 6.6.5 Other Variable Types 176 6.7 Direct Addressing 176 6.7.1 Addressing Structure 176 6.7.2 I/O‐Addressing 178 6.8 Variable versus I/O‐Addresses 179 6.8.1 Unspecified I/O‐Addresses 179 6.9 Declaration of Multielement Variables 180 6.9.1 Arrays 181 6.9.2 Data Structures 182 6.10 Test Problems 184 7 Functions 187 7.1 Introduction 187 7.2 On Functions 188 7.3 Standard Functions 189 7.3.1 Assignment 190 7.4 Boolean Operations 191 7.5 Arithmetic Functions 192 7.5.1 Overflow 193 7.6 Comparison 194 7.7 Numerical Operations 195 7.7.1 Priority of Execution 196 7.8 Selection 197 7.9 Type Conversion 197 7.10 Bit‐String Functions 199 7.11 Text‐String Functions 200 7.12 Defining New Functions 202 7.13 EN/ENO 203 7.14 Test Problems 204 8 Function Blocks 206 8.1 Introduction 206 8.1.1 The Standard’s FBs 207 8.2 Declaring and Calling FBs 207 8.3 FBs for Flank Detection 208 8.4 Bistable Elements 209 8.5 Timers 210 8.6 Counters 211 8.6.1 Up‐Counter 212 8.6.2 Down‐Counter 212 8.6.3 Up/Down‐Counter 212 8.7 Defining New FBs 213 8.7.1 Encapsulation of Code 214 8.7.2 Other Nonstandardized FBs 216 8.8 Programs 217 8.8.1 Program Calls 218 8.8.2 Execution Control 219 8.9 Test Problems 220 Part Four Programming 221 9 Ladder Diagram (LD) 223 9.1 Introduction 223 9.2 Program Structure 224 9.2.1 Contacts and Conditions 225 9.2.2 Coils and Actions 226 9.2.3 Graphical Elements: An Overview 227 9.3 Boolean Operations 227 9.3.1 AND/OR‐Conditions 227 9.3.2 Set/Reset Coils 230 9.3.3 Edge Detecting Contacts 233 9.3.4 Example: Control of a Mixing Process 234 9.4 Rules for Execution 237 9.4.1 One Output: Several Conditions 237 9.4.2 The Importance of the Order of Execution 238 9.4.3 Labels and Jumps 239 9.5 Use of Standard Functions in LD 240 9.6 Development and Use of FBs in LD 242 9.7 Structured Programming in LD 244 9.7.1 Flowchart versus RS‐Based LD Code 248 9.7.2 State Diagrams versus RS‐Based LD Code 253 9.8 Summary 259 9.9 Test Problems 260 10 Function Block Diagram (FBD) 262 10.1 Introduction 262 10.2 Program Structure 263 10.2.1 Concepts 264 10.3 Execution Order and Loops 264 10.3.1 Labels and Jumps 265 10.4 User‐Defined Functions and FBs 266 10.5 Integer Division 268 10.6 Sequential Programming with FBD 271 10.7 Test Problems 273 11 Structured Text (ST) 278 11.1 Introduction 278 11.2 ST in General 279 11.2.1 Program Structure 280 11.3 Standard Functions and Operators 281 11.3.1 Assignment 282 11.4 Calling FBs 283 11.4.1 Flank Detection and Memories 284 11.4.2 Timers 287 11.4.3 Counters 288 11.5 IF Statements 288 11.6 CASE Statements 290 11.7 ST Code Based upon State Diagrams 292 11.7.1 Example: Code for the Level Process 295 11.8 Loops 298 11.8.1 WHILE … DO… END_WHILE 298 11.8.2 FOR … END_FOR 299 11.8.3 REPEAT … END_REPEAT 300 11.8.4 The EXIT Instruction 300 11.9 Example: Defining and Calling Functions 301 11.10 Test Problems 302 12 Sequential Function Chart (SFC) 306 12.1 Introduction 306 12.1.1 SFC in General 307 12.2 Structure and Graphics 307 12.2.1 Overview: Graphic Symbols 309 12.2.2 Alternative Branches 309 12.2.3 Parallel Branches 311 12.3 Steps 312 12.3.1 Step Addresses 313 12.3.2 SFC in Text Form (for Those Specially Interested…) 314 12.4 Transitions 314 12.4.1 Alternative Definition of Transitions 315 12.5 Actions 317 12.5.1 Action Types 318 12.5.2 Action Control 319 12.5.3 Alternative Declaration and Use of Actions 321 12.6 Control of Diagram Execution 322 12.7 Good Design Technique 323 12.8 Test Problems 326 13 Examples 331 13.1 Example 1: PID Controller Function Block: Structured Text 331 13.2 Example 2: Sampling: SFC 333 13.2.1 List of Variables 334 13.2.2 Possible Solution 334 13.3 Example 3: Product Control: SFC 337 13.3.1 Functional Description 338 13.3.2 List of Variables 338 13.3.3 Possible Solution 339 13.4 Example 4: Automatic Feeder: ST/SFC/FBD 342 13.4.1 Planning and Structuring 344 13.4.2 Alternative 1: SFC 345 13.4.3 Alternative 2: ST/FBD 347 Part Five Implementation 351 14 CODESYS 2.3 353 14.1 Introduction 353 14.2 Starting the Program 354 14.2.1 The Contents of a Project 356 14.3 Configuring the (WAGO) PLC 357 14.4 Communications with the PLC 360 14.4.1 The Gateway Server 361 14.4.2 Local Connection via Service Cable 362 14.4.3 Via Ethernet 363 14.4.4 Communication with a PLC Connected to a Remote PC 364 14.4.5 Testing Communications 365 14.5 Libraries 365 14.6 Defining a POU 367 14.7 Programming in FBD/LD 368 14.7.1 Declaring Variables 369 14.7.2 Programming with FBD 371 14.7.3 Programming with LD 372 14.8 Configuring Tasks 375 14.9 Downloading and Testing Programs 376 14.9.1 Debugging 377 14.10 Global Variables and Special Data Types 379 15 CODESYS Version 3.5 381 15.1 Starting a New Project 381 15.1.1 Device 382 15.1.2 Application 384 15.2 Programming and Programming Units (POUs) 386 15.2.1 Declaration of Variables 388 15.3 Compiling and Running the Project 389 15.3.1 Start Gateway Server and PLS and Set Up Communications 390 15.4 Test Problems 393 Bibliography 395 Index 396

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Book SynopsisTable of ContentsAbout the Authors v Preface to the Seventh Edition vi How to Use This Book: Key Features viii 1 Innovation – What It Is and Why It Matters 1 1.1 The Importance of Innovation 2 1.2 Innovation Is Not Just High Technology 4 1.3 It’s Not Just Products . . . 7 1.4 Innovation and Entrepreneurship 9 1.5 Strategic Advantage Through Innovation 10 1.6 Old Question, New Context 15 1.7 The Globalization of Innovation 16 1.8 So, What Is Innovation? 19 1.9 A Process View of Innovation 22 1.10 The Scope for Innovation 24 Four Dimensions of Innovation Space 24 Mapping Innovation Space 28 1.11 Key Aspects of Innovation 29 Incremental Innovation – Doing What We Do but Better 30 Component/Architecture Innovation and the Importance of Knowledge 31 Platform Innovation 33 The Innovation Life Cycle – Different Emphasis Over Time 34 Discontinuous Innovation – What Happens When the Game Changes? 37 1.12 Innovation Management 42 Summary 44 Further Reading 45 Other Resources 47 References 48 2 Digital Is Different? 50 2.1 What Is Digital Innovation? 51 2.2 Is It New? 54 2.3 Is It Revolutionary? 55 2.4 What Does It Mean for Innovation? 56 2.5 What Does It Mean for Innovation Management? 59 The New Digital Toolkit 60 New Ways of Thinking About Innovation Management 64 Summary 67 Further Reading 67 Other Resources 68 References 68 3 Innovation as a Core Business Process 70 3.1 The Innovation Journey 70 3.2 Different Circumstances Similar Management Challenges 72 3.3 Variations on a Theme 73 Services and Innovation 73 Service Innovation Emphasizes the Demand Side 77 The Extended Enterprise 79 Innovation in the Non-commercial Arena 79 Not-for-Profit Innovation 80 Social Entrepreneurship 82 3.4 Cross Sector Differences 84 Organizational Size 84 Project-based Organizations 85 Platform Innovation 85 Ecosystems 86 The Influence of Geography 86 Regulatory Context 87 Industry Life Cycle 87 3.5 Do Better/Do Different 88 3.6 A Contingency Model of the Innovation Process 90 3.7 Evolving Models of the Process 90 3.8 Can We Manage Innovation? 93 3.9 Building and Developing Routines across the Core Process 95 Navigating the Negative Side of Routines 95 3.10 Learning to Manage Innovation 96 Identifying Simple Archetypes 97 Measuring Innovation Success 98 What Do We Know About Successful Innovation Management? 99 Success Routines in Innovation Management 101 Key Contextual Influences 107 3.11 Beyond the Steady State 108 Summary 108 Further Reading 109 Other Resources 109 References 110 4 Developing an Innovation Strategy 115 4.1 ‘Rationalist’ or ‘Incrementalist’ Strategies for Innovation? 116 Rationalist Strategy 117 Incrementalist Strategy 120 Implications for Management 121 4.2 Innovation ‘Leadership’ versus ‘Followership’ 123 4.3 The Dynamic Capabilities of Firms 126 Institutions: Finance, Management and Corporate Governance 126 Learning and Imitating 128 4.4 Appropriating the Benefits from Innovation 130 4.5 Exploiting Technological Trajectories 136 4.6 Developing Firm-specific Competencies 139 Hamel and Prahalad on Competencies 139 Assessment of the Core Competencies Approach 141 Developing and Sustaining Competencies 144 4.7 Globalization of Innovation 149 4.8 Enabling Strategy Making 154 Routines to Help Strategic Analysis 154 Portfolio Management Approaches 155 Summary 157 Further Reading 158 Other Resources 158 References 159 5 Building the Innovative Organization 164 5.1 Shared Vision, Leadership and the Will to Innovate 166 5.2 Appropriate Organizational Structure 172 5.3 Key Individuals 176 5.4 High Involvement in Innovation 179 5.5 A Roadmap for the Journey 183 5.6 Effective Team Working 186 5.7 Creative Climate 192 5.8 Boundary-Spanning 204 Contents xiii Summary 207 Further Reading 207 Other Resources 208 References 209 6 Sources of Innovation 214 6.1 Where Do Innovations Come From? 215 6.2 Knowledge Push 216 6.3 Need Pull 218 6.4 Making Processes Better 220 6.5 Crisis-driven Innovation 222 6.6 Whose Needs? The Challenge of Underserved Markets 223 6.7 Emerging Markets 227 6.8 Toward Mass Customization 229 6.9 Users as Innovators 232 6.10 Using the Crowd 235 6.11 Extreme Users 237 6.12 Prototyping 238 6.13 Watching Others – and Learning from Them 239 6.14 Recombinant Innovation 240 6.15 Design-led Innovation 241 6.16 Regulation 243 6.17 Futures and Forecasting 243 6.18 Accidents 244 Summary 245 Further Reading 246 Other Resources 247 References 248 7 Search Strategies for Innovation 251 7.1 The Innovation Opportunity 252 Push or Pull Innovation? 252 Incremental or Radical Innovation? 253 Exploit or Explore? 254 7.2 When to Search 254 7.3 Who Is Involved in Search? 255 7.4 Where to Search – The Innovation Treasure Hunt 257 Ambidexterity in Search 258 Framing Innovation Search Space 258 7.5 A Map of Innovation Search Space 260 Zone 1 261 Zone 2 261 Zone 3 262 Zone 4 262 7.6 How to Search 263 7.7 Absorptive Capacity 266 7.8 Tools and Mechanisms to Enable Search 268 Managing Internal Knowledge Connections 268 Extending External Connections 270 Summary 272 Further Reading 272 Other Resources 273 References 274 8 Innovation Networks 277 8.1 The ‘Spaghetti’ Model of Innovation 279 8.2 Innovation Networks 281 Why Networks? 282 Emergent Properties in Networks 284 Learning Networks 284 Breakthrough Technology Collaborations 286 Regional Networks and Collective Efficiency 286 Mobilizing Networking 287 8.3 Networks at the Start-up 288 8.4 Networks on the Inside . . . 290 8.5 Networks on the Outside 291 8.6 Networks into the Unknown 296 8.7 Managing Innovation Networks 298 Configuring Innovation Networks 298 Facing the Challenges of Innovation Networks 299 Summary 300 Further Reading 301 Other Resources 301 References 302 9 Dealing with Uncertainty 304 9.1 Meeting the Challenge of Uncertainty 305 9.2 The Funnel of Uncertainty 306 9.3 Planning Under Uncertainty 307 9.4 Forecasting Innovation 311 Customer or Market Surveys 313 Internal Analysis, for Example, Brainstorming 314 External Assessment, for Example, Delphi 314 Scenario Development 315 9.5 Estimating the Demand for Innovations 316 9.6 Assessing Risk, Recognizing Uncertainty 318 Risk as Probability 319 Perceptions of Risk 321 9.7 Assessing Opportunities for Innovation 325 Financial Assessment of Projects 325 How to Evaluate Learning? 326 How Practicing Managers Cope 334 9.8 Decision Making at the Edge 336 Selection and Reframing 336 9.9 Mapping the Selection Space 339 Summary 345 Further Reading 345 Other Resources 345 References 346 10 Creating New Products and Services 349 10.1 Processes for New Product Development 350 Concept Generation 353 Project Selection 353 Product Development 354 Product Commercialization and Review 355 Lean and Agile Product Development 355 Lean Start-up 356 10.2 Factors Influencing Product Success or Failure 358 Commitment of Senior Management 362 Clear and Stable Vision 362 Improvisation 363 Information Exchange 363 Collaboration under Pressure 364 10.3 Influence of Technology and Markets on Commercialization 364 10.4 Differentiating Products 368 10.5 Building Architectural Products 371 Segmenting Consumer Markets 372 Segmenting Business Markets 373 10.6 Commercializing Technological Products 378 10.7 Implementing Complex Products 381 The Nature of Complex Products 382 Links Between Developers and Users 382 Adoption of Complex Products 384 10.8 Service Innovation 385 10.9 Diffusion of Innovations 391 Processes of Diffusion 391 Factors Influencing Adoption 393 Characteristics of an Innovation 394 Summary 399 Further Reading 399 Other Resources 400 References 401 11 Exploiting Open Innovation and Collaboration 405 11.1 Joint Ventures and Alliances 406 Why Collaborate? 406 11.2 Forms of Collaboration 410 11.3 Patterns of Collaboration 413 11.4 Influence of Technology and Organization 415 Competitive Significance 416 Complexity of the Technology 417 Codifiability of the Technology 418 Credibility Potential 418 Corporate Strategy 419 Firm Competencies 419 Company Culture 419 Management Comfort 420 Managing Alliances for Learning 420 11.5 Collaborating with Suppliers to Innovate 427 11.6 User-led Innovation 431 11.7 Extreme Users 434 Co-development 435 Democratic Innovation and Crowdsourcing 436 11.8 Benefits and Limits of Open Innovation 438 Summary 441 Further Reading 442 Other Resources 442 References 443 12 Promoting Entrepreneurship and New Ventures 448 12.1 Ventures, Defined 449 Profile of a Venture Champion 450 Venture Business Plan 453 Funding 453 Crowd-funding 456 Corporate Venture Funding 456 Venture Capital 458 12.2 Internal Corporate Venturing 460 To Grow the Business 463 To Exploit Underutilized Resources in New Ways 463 To Introduce Pressure on Internal Suppliers 463 To Divest Noncore Activities 463 To Satisfy Managers’ Ambitions 464 To Spread the Risk and Cost of Product Development 464 To Combat Cyclical Demands of Mainstream Activities 464 To Learn About the Process of Venturing 464 To Diversify the Business 465 To Develop New Competencies 465 12.3 Managing Corporate Ventures 467 12.4 Assessing New Ventures 470 Structures for Corporate Ventures 472 Direct Integration 474 Integrated Business Teams 474 New Ventures Department 474 New Venture Division 474 Special Business Units 475 Independent Business Units 475 Nurtured Divestment 476 Complete Spin-off 476 Learning Through Internal Ventures 477 12.5 Spin-outs and New Ventures 479 12.6 University Incubators 482 12.7 Growth and Performance of Innovative Small Firms 489 Summary 499 Further Reading 499 Other Resources 500 References 501 13 Capturing the Business Value of Innovation 505 13.1 Creating Value through Innovation 506 13.2 Innovation and Firm Performance 510 13.3 Exploiting Knowledge and Intellectual Property 514 Generating and Acquiring Knowledge 514 Identifying and Codifying Knowledge 515 Storing and Retrieving Knowledge 518 13.4 Sharing and Distributing Knowledge 520 Converting Knowledge into Innovation 522 13.5 Exploiting Intellectual Property 525 Patents 525 Copyright 529 Design Rights 529 Licensing IPR 529 13.6 Business Models and Value Capture 532 Summary 540 Further Reading 540 Other Resources 541 References 542 14 Creating Social Value 545 14.1 Innovation and Social Change 546 14.2 The Social Innovation Process 548 Social Innovation as a Learning Laboratory 552 Public Sector Innovation 552 Supporting and Enabling Social Innovation 552 Challenges in Social Innovation 553 14.3 Inclusive Innovation 554 14.4 Humanitarian Innovation 556 14.5 The Challenge of Sustainability-led Innovation 557 14.6 A Framework Model for Sustainability-led Innovation 559 14.7 Responsible Innovation 567 Summary 568 Further Reading 569 Other Resources 569 References 570 15 Capturing Learning from Innovation 571 15.1 What We Have Learned About Managing Innovation 572 15.2 How to Build Dynamic Capability 573 15.3 How to Manage Innovation 575 15.4 The Importance of Failure 576 15.5 Tools to Help Capture Learning 577 Postproject Reviews (PPRs) 577 Proceduralizing Learning 578 Agile Innovation Methods 578 Benchmarking 579 Capability Maturity Models 579 15.6 Innovation Auditing 580 15.7 Measuring Innovation Performance 581 15.8 Measuring Innovation Management Capability 581 15.9 Reflection Questions for Innovation Auditing 583 Search 583 Select 584 Implement 584 Proactive Links 586 Learning 587 15.10 Developing Innovation Capability 588 15.11 Final Thoughts 590 Summary 591 Further Reading 591 Other Resources 591 References 592 Index I-1

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Book SynopsisDescribing the use of displays in microcontroller based projects, the author makes extensive use of real-world, tested projects. The complete details of each project are given, including the full circuit diagram and source code.Table of ContentsPreface xiii Acknowledgements xv 1 Introduction to Microcontrollers and Display Systems 1 1.1 Microcontrollers and Microprocessors 2 1.2 Evolution of the Microcontroller 3 1.3 Parts of a Microcontroller 4 1.3.1 Address 4 1.3.2 ALU 5 1.3.3 Analogue Comparator 5 1.3.4 Analogue-to-Digital Converter 5 1.3.5 Brown-out Detector 5 1.3.6 Bus 5 1.3.7 CAN 6 1.3.8 CISC 6 1.3.9 Clock 6 1.3.10 CPU 6 1.3.11 EEPROM 6 1.3.12 EPROM 6 1.3.13 Ethernet 7 1.3.14 Flash Memory 7 1.3.15 Harvard Architecture 7 1.3.16 Idle Mode 7 1.3.17 Interrupts 7 1.3.18 LCD Drivers 8 1.3.19 Pipelining 8 1.3.20 Power-on Reset 8 1.3.21 PROM 8 1.3.22 RAM 8 1.3.23 Real-time Clock 8 1.3.24 Register 9 1.3.25 Reset 9 1.3.26 RISC 9 1.3.27 ROM 9 1.3.28 Serial Input-Output 9 1.3.29 Sleep Mode 9 1.3.30 Supply Voltage 10 1.3.31 Timers 10 1.3.32 USB 10 1.3.33 Watchdog 10 1.4 Display Devices 10 1.4.1 LED 10 1.4.2 7-Segment LED 11 1.4.3 OLED 12 1.4.4 LCD 12 1.5 Summary 15 Exercises 15 2 PIC18F Microcontrollers 17 2.1 The PIC18F2410 Microcontroller 18 2.2 PIC18F2410 Architecture 19 2.2.1 The Program Memory 21 2.2.2 The Data Memory 21 2.2.3 Power Supply Requirements 22 2.2.4 Oscillator Configurations 24 2.2.5 The Reset 30 2.2.6 Parallel I/O Ports 31 2.2.7 Timer Modules 38 2.2.8 Analogue-to-Digital Converter Module 43 2.2.9 Special Features of the CPU 48 2.2.10 Interrupts 49 2.2.11 Pulse Width Modulator Module 53 2.3 Summary 56 Exercises 56 3 C Programming Language 59 3.1 C Languages for Microcontrollers 59 3.2 Your First mikroC Pro for PIC Program 61 3.2.1 Comments 61 3.2.2 Beginning and Ending a Program 62 3.2.3 White Spaces 63 3.2.4 Variable Names 63 3.2.5 Reserved Names 64 3.2.6 Variable Types 64 3.2.7 Constants 66 3.2.8 Escape Sequences 68 3.2.9 Volatile Variables 69 3.2.10 Accessing Bits of a Variable 69 3.2.11 sbit Type 70 3.2.12 bit Type 70 3.2.13 Arrays 70 3.2.14 Pointers 73 3.2.15 Structures 76 3.2.16 Unions 80 3.2.17 Operators in mikroC Pro for PIC 80 3.2.18 The Flow of Control 90 3.3 Functions in mikroC Pro for PIC 101 3.3.1 Function Prototypes 102 3.3.2 void Functions 103 3.3.3 Passing Parameters to Functions 104 3.3.4 Passing Arrays to Functions 106 3.3.5 Interrupt Processing 106 3.4 mikroC Pro for PIC Built-in Functions 108 3.5 mikroC Pro for PIC Libraries 109 3.5.1 ANSI C Library 109 3.5.2 Miscellaneous Library 111 3.6 Using the mikroC Pro for PIC Compiler 111 3.6.1 mikroC Pro for PIC IDE 112 3.6.2 Creating a New Source File 118 3.6.3 Compiling the Source File 122 3.7 Using the mikroC Pro for PIC Simulator 123 3.7.1 Setting a Break-Point 124 3.8 Other mikroC Pro for PIC Features 126 3.8.1 View Statistics 126 3.8.2 View Assembly 127 3.8.3 ASCII Chart 127 3.8.4 USART Terminal 127 3.8.5 Seven Segment Editor 127 3.8.6 Help 128 3.9 Summary 128 Exercises 129 4 PIC Microcontroller Development Tools – Including Display Development Tools 131 4.1 PIC Hardware Development Boards 132 4.1.1 Super Bundle Development Kit 132 4.1.2 PIC18 Explorer Board 132 4.1.3 PIC18F4XK20 Starter Kit 134 4.1.4 PICDEM 4 135 4.1.5 PIC16F887 Development Kit 135 4.1.6 FUTURLEC PIC18F4550 Development Board 137 4.1.7 EasyPIC6 Development Board 137 4.1.8 EasyPIC7 Development Board 139 4.2 PIC Microcontroller Display Development Tools 140 4.2.1 Display Hardware Tools 140 4.2.2 Display Software Tools 143 4.3 Using the In-Circuit Debugger with the EasyPIC7 Development Board 145 4.4 Summary 149 Exercises 149 5 Light Emitting Diodes (LEDs) 151 5.1 ATypical LED 151 5.2 LED Colours 153 5.3 LED Sizes 154 5.4 Bi-Colour LEDs 154 5.5 Tri-Colour LEDs 155 5.6 Flashing LEDs 155 5.7 Other LED Shapes 155 5.8 7-Segment LEDs 156 5.8.1 Displaying Numbers 157 5.8.2 Multi-digit 7-Segment Displays 159 5.9 Alphanumeric LEDs 159 5.10 mikroC Pro for PIC 7-Segment LED Editor 163 5.11 Summary 163 Exercises 164 6 Liquid Crystal Displays (LCDs) and mikroC Pro for PIC LCD Functions 165 6.1 HD44780 Controller 165 6.2 Displaying User Defined Data 168 6.3 DDRAM Addresses 169 6.4 Display Timing and Control 171 6.4.1 Clear Display 172 6.4.2 Return Cursor to Home 172 6.4.3 Cursor Move Direction 172 6.4.4 Display ON/OFF 172 6.4.5 Cursor and Display Shift 173 6.4.6 Function Set 173 6.4.7 Set CGRAM Address 173 6.4.8 Set DDRAM Address 173 6.4.9 Read Busy Flag 174 6.4.10 Write Data to CGRAM or DDRAM 174 6.4.11 Read Data from CGRAM or DDRAM 174 6.5 LCD Initialisation 174 6.5.1 8-bit Mode Initialisation 175 6.5.2 4-bit Mode Initialisation 175 6.6 Example LCD Display Setup Program 177 6.7 mikroC Pro for PIC LCD Functions 180 6.7.1 Lcd_Init 180 6.7.2 Lcd_Out 181 6.7.3 Lcd_Out_Cp 181 6.7.4 Lcd_Chr 181 6.7.5 Lcd_Chr_Cp 181 6.7.6 Lcd_Cmd 182 6.8 Summary 182 Exercises 183 7 Graphics LCD Displays (GLCD) 185 7.1 The 128 x 64 Pixel GLCD 185 7.2 Operation of the GLCD Display 187 7.3 mikroC Pro for PIC GLCD Library Functions 189 7.3.1 Glcd_Init 189 7.3.2 Glcd_Set_Side 190 7.3.3 Glcd_Set_X 190 7.3.4 Glcd_Set_Page 190 7.3.5 Glcd_Write_Data 190 7.3.6 Glcd_Fill 190 7.3.7 Glcd_Dot 191 7.3.8 Glcd_Line 191 7.3.9 Glcd_V_Line 191 7.3.10 Glcd_H_Line 191 7.3.11 Glcd_Rectangle 192 7.3.12 Glcd_Rectangle_Round_Edges 192 7.3.13 Glcd_Rectangle_Round_Edges_Fill 192 7.3.14 Glcd_Box 193 7.3.15 Glcd_Circle 193 7.3.16 Glcd_Circle_Fill 194 7.3.17 Glcd_Set_Font 194 7.3.18 Glcd_Set_Font_Adv 194 7.3.19 Glcd_Write_Char 195 7.3.20 Glcd_Write_Char_Adv 195 7.3.21 Glcd_Write_Text 195 7.3.22 Glcd_Write_Text_Adv 195 7.3.23 Glcd_Write_Const_Text_Adv 196 7.3.24 Glcd_Image 196 7.4 Example GLCD Display 196 7.5 mikroC Pro for PIC Bitmap Editor 198 7.6 Adding Touch-screen to GLCDs 199 7.6.1 Types of Touch-screen Displays 200 7.6.2 Resistive Touch Screens 200 7.7 Summary 203 Exercises 204 8 Microcontroller Program Development 205 8.1 Using the Program Description Language and Flowcharts 205 8.1.1 BEGIN – END 206 8.1.2 Sequencing 206 8.1.3 IF – THEN – ELSE – ENDIF 206 8.1.4 DO – ENDDO 207 8.1.5 REPEAT – UNTIL 209 8.1.6 Calling Subprograms 209 8.1.7 Subprogram Structure 209 8.2 Examples 211 8.3 Representing for Loops in Flowcharts 216 8.4 Summary 218 Exercises 218 9 LED Based Projects 219 9.1 PROJECT 9.1 – Flashing LED 219 9.2 PROJECT 9.2 – Binary Counting Up LEDs 226 9.3 PROJECT 9.3 – Rotating LEDs 229 9.4 PROJECT 9.4 – Wheel of Lucky Day 231 9.5 PROJECT 9.5 – Random Flashing LEDs 239 9.6 PROJECT 9.6 – LED Dice 240 9.7 PROJECT 9.7 – Connecting more than one LED to a Port Pin 246 9.8 PROJECT 9.8 – Changing the Brightness of LEDs 250 9.9 PROJECT 9.9 – LED Candle 264 9.10 Summary 267 Exercises 267 10 7-Segment LED Display Based Projects 269 10.1 PROJECT 10.1 – Single Digit Up Counting 7-Segment LED Display 269 10.2 PROJECT 10.2 – Display a Number on 2-Digit 7-Segment LED Display 271 10.3 PROJECT 10.3 – Display Lottery Numbers on 2-Digit 7-Segment LED Display 278 10.4 PROJECT 10.4 – Event Counter Using 4-Digit 7-Segment LED Display 285 10.5 PROJECT 10.5 – External Interrupt Based Event Counter Using 4-Digit 7-Segment LED Display with Serial Driver 292 10.6 Summary 302 Exercises 303 11 Text Based LCD Projects 305 11.1 PROJECT 11.1 – Displaying Text on LCD 305 11.2 PROJECT 11.2 – Moving Text on LCD 307 11.3 PROJECT 11.3 – Counting with the LCD 310 11.4 PROJECT 11.4 – Creating Custom Fonts on the LCD 315 11.5 PROJECT 11.5 – LCD Dice 317 11.6 PROJECT 11.6 – Digital Voltmeter 325 11.7 PROJECT 11.7 – Temperature and Pressure Display 327 11.8 PROJECT 11.8 – The High/Low Game 333 11.9 Summary 344 Exercises 345 12 Graphics LCD Projects 347 12.1 PROJECT 12.1 – Creating and Displaying a Bitmap Image 347 12.2 PROJECT 12.2 – Moving Ball Animation 355 12.3 PROJECT 12.3 – GLCD Dice 357 12.4 PROJECT 12.4 – GLCD X-Y Plotting 372 12.5 PROJECT 12.5 – Plotting Temperature Variation on the GLCD 374 12.6 PROJECT 12.6 – Temperature and Relative Humidity Measurement 385 12.7 Operation of the SHT11 386 12.8 Acknowledgement 389 12.9 Summary 400 Exercises 400 13 Touch Screen Graphics LCD Projects 401 13.1 PROJECT 13.1 – Touch Screen LED ON-OFF 401 13.2 PROJECT 13.2 – LED Flashing with Variable Rate 410 13.3 Summary 418 Exercises 418 14 Using the Visual GLCD Software in GLCD Projects 419 14.1 PROJECT 14.1 – Toggle LED 420 14.2 PROJECT 14.2 – Toggle more than One LED 425 14.3 PROJECT 14.3 – Mini Electronic Organ 426 14.4 PROJECT 14.4 – Using the SmartGLCD 430 14.5 PROJECT 14.5 – Decimal to Hexadecimal Converter using the SmartGLCD 444 14.6 Summary 452 Exercises 452 15 Using the Visual TFT Software in Graphics Projects 453 15.1 PROJECT 15.1 – Countdown Timer 454 15.2 PROJECT 15.2 – Electronic Book 462 15.3 PROJECT 15.3 – Picture Show 467 15.4 Summary 472 Exercises 472 Bibliography 473 Index 475

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Book SynopsisEnhanced e-book includes videos Many books have been written on modelling, simulation and control of four-wheeled vehicles (cars, in particular). However, due to the very specific and different dynamics of two-wheeled vehicles, it is very difficult to reuse previous knowledge gained on cars for two-wheeled vehicles. Modelling, Simulation and Control of Two-Wheeled Vehicles presents all of the unique features of two-wheeled vehicles, comprehensively covering the main methods, tools and approaches to address the modelling, simulation and control design issues. With contributions from leading researchers, this book also offers a perspective on the future trends in the field, outlining the challenges and the industrial and academic development scenarios. Extensive reference to real-world problems and experimental tests is also included throughout. Key features: The first book to cover all aspects of two-wheeled vehicle dynamiTable of ContentsAbout the Editors xi List of Contributors xiii Series Preface xv Introduction xvii Part One TWO-WHEELED VEHICLES MODELLING AND SIMULATION 1 Motorcycle Dynamics 3 Vittore Cossalter, Roberto Lot, and Matteo Massaro 1.1 Kinematics 3 1.2 Tyres 6 1.3 Suspensions 13 1.4 In-Plane Dynamics 18 1.5 Out-of-Plane Dynamics 29 1.6 In-Plane and Out-of-Plane Coupled Dynamics 40 References 41 2 Dynamic Modelling of Riderless Motorcycles for Agile Manoeuvres 43 Yizhai Zhang, Jingang Yi, and Dezhen Song 2.1 Introduction 43 2.2 Related Work 44 2.3 Motorcycle Dynamics 45 2.4 Tyre Dynamics Models 51 2.5 Conclusions 55 Nomenclature 55 Appendix A: Calculation of Ms 56 Appendix B: Calculation of Acceleration ̇G 57 Acknowledgements 57 References 57 3 Identification and Analysis of Motorcycle Engine-to-Slip Dynamics 59 Matteo Corno and Sergio M. Savaresi 3.1 Introduction 59 3.2 Experimental Setup 60 3.3 Identification of Engine-to-Slip Dynamics 61 3.4 Engine-to-Slip Dynamics Analysis 73 3.5 Road Surface Sensitivity 78 3.6 Velocity Sensitivity 79 3.7 Conclusions 80 References 80 4 Virtual Rider Design: Optimal Manoeuvre Definition and Tracking 83 Alessandro Saccon, John Hauser, and Alessandro Beghi 4.1 Introduction 83 4.2 Principles of Minimum Time Trajectory Computation 86 4.3 Computing the Optimal Velocity Profile for a Point-Mass Motorcycle 90 4.4 The Virtual Rider 102 4.5 Dynamic Inversion: from Flatland to State-Input Trajectories 103 4.6 Closed-Loop Control: Executing the Planned Trajectory 107 4.7 Conclusions 115 4.8 Acknowledgements 116 References 116 5 The Optimal Manoeuvre 119 Francesco Biral, Enrico Bertolazzi, and Mauro Da Lio 5.1 The Optimal Manoeuvre Concept: Manoeuvrability and Handling 121 5.2 Optimal Manoeuvre as a Solution of an Optimal Control Problem 133 5.3 Applications of Optimal Manoeuvre to Motorcycle Dynamics 145 5.4 Conclusions 152 References 152 6 Active Biomechanical Rider Model for Motorcycle Simulation 155 Valentin Keppler 6.1 Human Biomechanics and Motor Control 156 6.2 The Model 161 6.3 Simulations and Results 167 6.4 Conclusions 179 References 180 7 A Virtual-Reality Framework for the Hardware-in-the-Loop Motorcycle Simulation 183 Roberto Lot and Vittore Cossalter 7.1 Introduction 183 7.2 Architecture of the Motorcycle Simulator 184 7.3 Tuning and Validation 188 7.4 Application Examples 191 References 194 Part Two TWO-WHEELED VEHICLES CONTROL AND ESTIMATION PROBLEMS 8 Traction Control Systems Design: A Systematic Approach 199 Matteo Corno and Giulio Panzani 8.1 Introduction 199 8.2 Wheel Slip Dynamics 202 8.3 Traction Control System Design 206 8.4 Fine tuning and Experimental Validation 212 8.5 Conclusions 218 References 219 9 Motorcycle Dynamic Modes and Passive Steering Compensation 221 Simos A. Evangelou and Maria Tomas-Rodriguez 9.1 Introduction 221 9.2 Motorcycle Main Oscillatory Modes and Dynamic Behaviour 222 9.3 Motorcycle Standard Model 224 9.4 Characteristics of the Standard Machine Oscillatory Modes and the Influence of Steering Damping 226 9.5 Compensator Frequency Response Design 228 9.6 Suppression of Burst Oscillations 233 9.7 Conclusions 240 References 240 10 Semi-Active Steering Damper Control for Two-Wheeled Vehicles 243 Pierpaolo De Filippi, Mara Tanelli, and Matteo Corno 10.1 Introduction and Motivation 243 10.2 Steering Dynamics Analysis 245 10.3 Control Strategies for Semi-Active Steering Dampers 252 10.3.1 Rotational Sky-Hook and Ground-Hook 253 10.4 Validation on Challenging Manoeuvres 257 10.5 Experimental Results 266 10.6 Conclusions 267 References 268 11 Semi-Active Suspension Control in Two-Wheeled Vehicles: a Case Study 271 Diego Delvecchio and Cristiano Spelta 11.1 Introduction and Problem Statement 271 11.2 The Semi-Active Actuator 272 11.3 The Quarter-Car Model: a Description of a Semi-Active Suspension System 275 11.4 Evaluation Methods for Semi-Active Suspension Systems 277 11.5 Semi-Active Control Strategies 279 11.6 Experimental Set-up 281 11.7 Experimental Evaluation 281 11.8 Conclusions 289 References 289 12 Autonomous Control of Riderless Motorcycles 293 Yizhai Zhang, Jingang Yi, and Dezhen Song 12.1 Introduction 293 12.2 Trajectory Tracking Control Systems Design 294 12.3 Path-Following Control System Design 305 12.4 Conclusion 315 Acknowledgements 317 Appendix A: Calculation of the Lie Derivatives 317 References 318 13 Estimation Problems in Two-Wheeled Vehicles 319 Ivo Boniolo, Giulio Panzani, Diego Delvecchio, Matteo Corno, Mara Tanelli, Cristiano Spelta, and Sergio M. Savaresi 13.1 Introduction 319 13.2 Roll Angle Estimation 320 13.3 Vehicle Speed Estimation 329 13.4 Suspension Stroke Estimation 337 13.5 Conclusions 342 References 342 Index 345

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Book SynopsisTable of ContentsPreface , Organizers, Numerical optimization techniquesA comparative study between wavelet-adaptive multiple shooting and single shooting implemented in a MATLAB-EMSO environment L.S. Santos, A.R. Secchi & E.C. Biscaia Jr.Results comparison between SIMP and SERA for compliant mechanisms design C. Alonso, R. Ansola, E. Veguería & O.M. QuerinApplication of derivative-free multi-objective algorithms to reliability-based robust design optimization of a high-speed catamaran in real ocean environment R. Pellegrini, E.F. Campana, M. Diez, A. Serani, F. Rinaldi, G. Fasano, U. Iemma, G. Liuzzi, S. Lucidi & F. SternMulti-Objective Optimization (MDO) and differential geometry controlled Pareto front solution spacing C. Bakker & G.T. ParksSolving dual hesitant fuzzy assignment problem with restrictions using similarity measure P. SinghStructural optimization of frame structures by integer programming with design code failure constrains A. Kuckoski & J.S.O. FonsecaA study on multidisciplinary design optimization method for UUV M.Y.Wang, Z.F.Wei, Q. Yu & S.L. YangThe comprehensive optimization analysis of mechanical properties of the monohull ship S.L. Yang, Q. Yu &Y. ChenComprehensive optimization of the performance for USV and its methods S. Zhang, S.L. Yang, G.Y. Zhang & Y.Y.WenReal-time optimization by indirect NMPC methods C. Schwarz, R. Callies & A. SzaboInterval partitioning methods for mixed integer nonlinear problems B. Ergüne¸s, L. Özdamar, N. Gülcan & O. DemirMulti-stage stochastic distribution model L.T. Guardia & T.G. de TorresA novel hybrid method for optimal control problems and its application to trajectory optimization in micro manufacturing E. Bauma & T. SchusterA one-step discrete adjoint-based approach for combined design optimization and a posteriori error estimation J. Miranda, S. Abraham, K. Elsayed & C. LacorApplication of cellular automaton to combinatorial optimization problems K. Ishihashi, H. Furuta, Y. Nomura, K. Nakatsu & K. TakahashiA surrogate-assisted evolutionary algorithm for dynamic structural identification P. Gambarelli & L. VincenziMOGASI: A multi-objective genetic algorithm for efficiently handling constraints and diversified decision variables S. Costanzo, L. Castelli & A. TurcoA metric to assist the selection of the particle swarm optimization parameters C.A. da Silva Jr.,W.B. Saba, N.M. Abe & A. PassaroStructural design optimization of lightweight structures considering material selection and sizing M. Schatz, E.J.Wehrle & H. BaierApplication of the flower pollination algorithm in nonlinear algebraic systems with multiple solutions G.M. PlattSchemes in setting position and radius of RBF in convolute RBF for surrogate optimization M. Arakawa & S. KitayamaInvestigation of energy dissipation over stepped spillways using a hybrid FV-ANN technique A. Dolatshah, H. Imani Khoshkho & M. MashalRobust optimization of shunt circuits for the passive control of composite structures B.G.G.L. Zambolini-Vicente, V.A.C. Silva & A.M.G. de LimaRecent advances in the solution of large nonlinear optimisation problems withWORHP T. Linke, D.L.Wassel & C. BüskensAn improved methodology for airfoil shape optimization using surrogate based design optimization D. Rajaram & R.S. PantA new draft of resolution to the p-median problem J. Fernandes dos Santos & C. dos Santos MachadoOptimization of the ready-mixed concrete delivery system using transportation algorithm G. Albayrak & U. AlbayrakDesign optimization and inverse problemsPARETO and NASH fronts as the limit case of the isoperimetric inequality in multiobjective optimization theory V.V. KobelevDesign of material anisotropy constitutive matrices for structural stiffness and strength optimization P. Pedersen & N.L. PedersenA genetic algorithm for optimization of spatial trusses considering self-weight loads A.C.C. Lemonge, P.H. Hallak, L.G. Fonseca & H.J.C. BarbosaExistence and uniqueness of the regularized solution in the problem of recovery of the non-steady emission rate of a point source: Application of the adjoint method D. Parra-Guevara, Y.N. Skiba & A. Reyes-RomeroShape optimization of interior permanent magnet motor for torque ripple reduction E. Kuci, P. Duysinx, C. Geuzaine & P. DularStructural identification of two dimensional shear buildings using a modified adaptive harmony search algorithm M.M. Jahjouh & U. NackenhorstPractical interest of “anti-optimal” solutions in optimal structural design T. Messager & M. PyrzOptimization of an unitary split system air conditioner with variable refrigerant flow F.O.B. Brochier, M.L.S. Indrusiak & P.R.WanderOn the use of min-max algorithms in receding horizon control laws for harbor defense S. Lee, E. Polak & J.WalrandOn optimization of internal/external spur gears tooth bending strength N.L. PedersenApplication of Generalized Extremal Optimization (GEO) technique to design the orbit transfer solar sail control system I. Mainenti-Lopes, L.C.G. Souza & F.L. De SousaComparison between unrestricted dynamic shakedown design and a new probabilistic approach for structures under seismic loadings L. Palizzolo, S. Benfratello & P. TabbusoOptimization and investigation of the dynamical-optical behavior of mirror systems J. Störkle, N.Wengert & P. EberhardNumerical direct evolutionary identification of constitutive semi-crystalline polymer model parameters H. Abdul-Hameed, T. Messager, F. Zaïri & M. Naït-AbdelazizDesign of after-market wind turbine blade add-ons for noise reduction S.S. Rodrigues & A.C. MartaOptimal design of curved folded plates by optimality criteria method B. Balogh & J. LógóRecovering the functional form of nonlinear heat transfer by means of thermal imaging G. IngleseMultidisciplinary performance based optimization of aircraft F. Afonso, J. Vale, F. Lau & A. SulemanStochastic optimization in aircraft design L. Amândio, A. Marta, F. Afonso, J. Vale & A. SulemanPerformance optimization of complex continuous mining system using stochastic simulation M.S. Shishvan & J. BenndorfParameterization formulations for aerofoil shape optimization D.A. Vicente, P.V. Gamboa & M.A.R. Silvestre2-D shape optimization of aerostat envelopes using Kriging S.N. Paul, D. Patil & R.S. PantDesign optimization of the centrifugal clutch of the M3165 four-stroke internal combustion engine P. de F.V. CarvalheiraOptimization of a car radiator fin thickness P.WaisSimulation of polymeric membrane in Aspen Plus for CO2 post-combustion capture A. Pascu, A. Badea, C. Dinca & L. StoicaHybrid optimization algorithm applied on multistage axial compressor performance calculations with variable geometry O.F.R. Silva, J.T. Tomita, C. Bringhenti & D.F. CavalcaOn the optimization of a piezoelectric speaker for hearing aid application through multi-physical FE models G.C. Martins, P.R. Nunes & J.A. CordioliTopology optimization for improving the performance of solar cells D.K. Gupta, M. Langelaar, F. van Keulen & M. BarinkInformation-maximizing adaptive design of experiments for wind tunnel testing H.-L. Choi, J. Ahn & D.-H. ChoA graphic Java interface for the calculation of double azeotropes by the inversion of functions from the plane to the plane G.B. Libotte, G.M. Platt & A. de L. GuedesOptimisation of hierarchical structures for compression bearing applications D. Rayneau-Kirkhope, Y. Mao & R.S. FarrShape optimization for homogenized phononic materials and band gap structures E. Rohan, J. Vondˇrejc & J. HeczkoRobust reliability-based aerodynamic shape optimization D.I. Papadimitriou & C. PapadimitriouWeight minimization of truss structures subjected to dynamic loading M.M. Hedaya, A. Elsabbagh & A.M. HusseinInversion of functions from the plane to the plane to solve nonlinear algebraic systems: Calculating of double azeotrope using the modified Raoult’s Law in the mixture benzene+hexafluorobenzene A.L. Guedes, G.M. Platt & F.D.M. NetoExperimental studies of a variable water volume chiller system for energy conservation Y.F.Wang & Q. ChenThe topology optimization of electronic parts mounted on micro satellite H. Nakamura & T. MiyashitaDetermination of peel strength based on composition of adhesives for the footwear industry using genetic algorithm R.M. Paiva, C.C. António & L.M. SilvaPerformance based MDO of a regional transport aircraft with a joined wing configuration J. Vale, F. Afonso, F. Lau & A. SulemanA polynomial algorithm for a special case of the one-machine scheduling problem with time-lags H. RamalhinhoOptimization of multimodal shunt circuits for the passive control of composite structures V.A.C. Silva, B.G.G.L. Zambolini-Vicente & A.M.G. de LimaOptimal pitching axis of flapping-wings for hovering flight Q.Wang, J.F.L. Goosen & F. van KeulenModeling and parameter estimation of a biogas plant using maize silage in a two step model J.A. Arzate, M.N. Cruz Bournazou, M. Kirstein, P. Neubauer, S. Junne & B. HabermannHeat exchanger design optimization taking into account uncertainties of different correlations J. Lambert & L. GosselinTuning parameters using bio-inspired multiobjective optimization algorithm for topology optimization based on bacterial chemotaxis J.X. Leon & M.A. GuzmanOptimization of microstructures using statistical and physical descriptors within a cellular automaton framework A. Emami, T.Wu &A. TovarOptimization of a material with a negative stiffness provided by an inherent bistable element J. Heczko, Z. Dimitrovová & H.C. RodriguesApplication of relaxation matrix logic-structural in the allocation optimization of devices in power systems distribution M.M. Santos, A.R. Abaide, M. Sperandio &T.F. MilkeEfficient analysis and reanalysis techniquesUsing model order reduction to accelerate optimization of multi-stage linear dynamical systems Y. Yue, S. Li, L. Feng, A. Seidel-Morgenstern & P. BennerImproving inversion algorithms for geosounding inversion H. Hidalgo-Silva & E. Gómez-TreviñoOn solution of 3D contact shape optimization problems with Coulomb friction based on domain decomposition P. Beremlijski & A. MarkopoulosEfficient reliability-based optimization using a combined metamodel and FE-based strategy S. ShettySensitivity analysisA revised vertex enumeration algorithm via dual Fourier-Motzkin elimination method S.D. AbdullahiTopological derivatives for fundamental frequencies of elastic bodies V.V. KobelevSensitivity analysis of the model response in mechanized tunneling simulation – A case study assessment C. Zhao, A.A. Lavasan & T. SchanzReaeration coefficient sensitivity analysis for water quality river modelling V.T.R. Costa, J. Lugon Jr. & P.P.W. RodriguesIndustrial applicationsFlow optimization of hydraulic accumulators H. Ortwig, U. Zimmermann & D. HübnerTopology optimization of a wing structure F.C. Sousa, F.P. Lau & A. SulemanThe potential of support vector machines and Kriging in modelling the gas cyclone performance K. Elsayed, D. Vucinic & C. LacorMethod and system for control of flotation process based on preliminary estimates of ore grade V. Morozov, Z. Ganbaatar, L. Delgerbat & V. StoliarovA firefly based optimization algorithm for optimal planning of voltage controlled distributed generators M.M. Othman,W. El-Khattam, A.Y. Abdelaziz & Y.G. HegazyOptimization of the overload-protection degree A.V. Perelmuter & T.Y. VeriuzhskaA model for scheduling of employees using supplier selection S. HolopainenOptimization of a silver catalyzed formaldehyde plant using artificial neural networks R.L. Reis, R.M. Fontes, J.K.O. Fernandes, R.A. Kalid & K.V. PontesHypersonic cryogenic tank design using mixed-variable surrogate-based optimization Ch. Beauthier, A. Mahajan, C. Sainvitu, P. Hendrick, S. Sharifzadeh & D. VerstraetePolymer electrolyte fuel cell performances enhanced by under-rib convection J. Ahn, J. Lee, N.D. Vihn, S. Park, H.-M. Kim & K.-S. ChoiRobust assignment of fleet size and travel routes for transportation to a single-destiny using optimization via simulation E.G. Baquela & A.C. OliveraAn optimization model for truck tyres selection Z. Šabartová, A.-B. Strömberg, M. Patriksson & P. LindrothOptimization of storage space in port grain cereal storage silos – a case study M.G. Cardoso, E.P. Ferreira, M.P. Lopes & C. LopesA Hybrid Harmony Search (HHS) algorithm for a Green Vehicle Routing Problem (GVRP) R. Kawtummachai & T. ShohdohjiAutomotive shift quality optimization based on piecewise monotone interpolation of parameter characteristics A.Wurm, D. Bestle & S. KahlbauTemperature prediction in high speed incremental forming process by data mining techniques C. Ciancio, G. Ambrogio, L. Filice, F. Gagliardi & R. MusmannoOptimal race course design for air races R. CalliesAutomotive Powertrain optimization by genetic algorithm analysing transmission ratios G.B. Colherinhas, P.H.C. Dias, A.C.G.C. Diniz & A.P.S.P. RodriguesMulti-objective optimization to simultaneously address energy hub layout, sizing and scheduling using a linear formulation G. Mavromatidis, R. Evins, K. Orehounig, V. Dorer & J. CarmelietOptimal control in moving domains: An application to eutrophication L.J. Alvarez-Vázquez, A. Martínez & F.J. FernándezOptimum design of a dissipative link in wall-frame systems R. Greco & G.C. MaranoInverse procedure for determining transient fluid temperature based on temperature responses of the thermometer and pipeline wall J. Taler & M. JaremkiewiczModel-linearization strategies for MPC of the air-path of a diesel engine R. Bapst, M. Jakob, C. Onder, L. Guzzella & J. AsprionOptimization of the fuel consumption of M3165 four-stroke internal combustion engine P. de F.V. Carvalheira & J.M.F. NunesUse of genetic algorithms for spare parts distribution system A. Rybicková, A. Karásková & D. MockováMixture optimization and analysis of the chemical behavior of different types of ethanol for export M.C.O. Pedulla, J.I. Soletti & S.H.V. CarvalhoTowards a monolithic design of large aircraft wing spoilers using numerical topology and laminate optimization M. Meindlhumer, M. Schagerl & M. FleischmannDesign optimization of equivalent mooring system on truncated depth F.M.G. Ferreira, E.N. Lages, S.M.B. Afonso & P.R.M. LyraAchievement of metamodels for optimization of methylamines production process through computer aided design A.V.L. Machado, D.P. Leitoles, M.K. Lenzi, C.I. Yamamoto & L.F.L. Luz Jr.Optimization in biogas processes production. The importance of global sensitivity analysis, optimization procedure and uncertainty analysis A. Donoso-Bravo, G. Ruiz-Filippi & F. Carrera-ChapelaShape optimization of aircraft cabin ventilation components using adjoint CFD T. Köthe, S. Herzog & C.WagnerOptimization methods applied to nonlinear signal interference models M. da Silva, E.L.F. Senne & N.L. VijaykumarThe Combinatorial-Cyclic method of Optimization (CCOpt) in a scaled or full sized prototyping and virtual prototyping S. Zietarski, S. Kachel, A. Kozakiewicz & S. WrzesienShape optimization of inductors for preheating before laser welding and hardening D. Pánek, P. K°us, V. Kotlan, R. Hamar & I. DoleželAdjoint-based shape optimization of high-speed trains D. Jakubek, S. Herzog & C.WagnerOptimizing parameters of a downdraft biomass gasifier F.O. Centeno-González, K.A. Almeida, E.E.S. Lora & J.L. GonçalvesOptimal selection and operation of distributed energy resources for an urban district B. Morvaj, R. Evins & J. CarmelietRobust shape optimization of composite structure using metamodels A. Janushevskis, A. Melnikovs & J. JanusevskisModeling and analysis of control in one unit compression chlorine S.K.S. Carmo, L.G.S. Vasconcelos & M. da S.A. EmerencianoMinimizing the environmental impact of R-C structural elements M. Kripka, G.F. Medeiros, J.L.T. Fraga & P.R. MarosinAn adaptive multiscale approximation assisted multiobjective optimization applied to compact heat exchangers K.H. Saleh, D. Bacellar, V. Aute & R. RadermacherResidual stress and distortion after ejection for injection molded part with metal-insert by the process chain analysis K. Jin, T. Jeong & N. KimNumerical analysis and optimal design to reduce residual stresses and deformations of die casting sheets after ejection T. Kim, K. Jin, A. Teagen & N. KimThe ant colony optimization algorithm for offshore air transport in the northeast of Brazil L.O. Mota, K.A. Rocha, T.X.R. Souza, E. Jesus, A.M. Oliveira Jr., J.I. Soletti, S.H.V. Carvalho & D.F. SouzaProductivity and optimization of the brew production by mash variation V.B. Barreto, F.D.R. Amado & K.V. CruzOptimization of the DLR SpaceLiner inside the integration environment RCE S. Zur & A. TröltzschOptimization of corporate performance using data envelopment analysis with Maple J. Hrebícek, O. Trenz, Z. Chvátalová & J. SoukopováOn the optimization and accuracy of stress-strain curve determination using hydraulic bulge test H. Campos, B. Martins, A.D. Santos & F. BarlatThin-walled component design optimization for crashworthiness using principles of compliant mechanism synthesis and Kriging sequential approximation K. Liu, A. Tovar & D. DetwilerReliability-based topology optimization for uncertain building systems in seismic zones S. Bobby, S.M.J. Spence, E. Bernardini & A. KareemQuantum-inspired evolution for smart building energy management in future power networks R. Badawy, A. Heßler, S. Albayrak, B. Hirsch & A. YassineStudy of the dynamic behavior and development of the optimal procedure of startup a thermally coupled distillation column A.L.U. Vasconcelos, I.C. Nunes, L.G.S. Vasconcelos & R.P. BritoModeling and optimization of a distillation column using advanced optimization software (ROMeo) C. Quito, I. Bessa & K. PontesExperimental methodology for quantification analysis of methane emissions applied to the charcoal production in laboratory I.M.O. Maia, S.R. de Carvalho, V.L. Borges, R.L. Mota, L.D. Barbosa & E.A.P. de LimaAssessment of corrosion and mechanical properties of rebar used in a 50-year-old reinforced concrete industrial building M. Canbaz & U. AlbayrakExamination of material properties and carbonation of concrete in a 50-year-old structure M. Canbaz, U. Albayrak & E. UnluogluSeven-stage axial compressor optimization V.N. Matveev, O.V. Baturin, G.M. Popov & I.N. EgorovDynamic job shop scheduling with alternative routes based on genetic algorithm A. Ali, P. Hackney, D. Bell & M. BirkettMS01 – Topology optimization for structural static and dynamic failuresMajor advances in exact structural topology optimization: Stress and displacement based multi-load design G.I.N. Rozvany, V. Pomezanski, T. Sokoł & E. PintérOptimum structures of micropolar materials depending on elastic constants Y. Arimitsu, Z.Q.Wu, Y. Sogabe & T. KimuraTowards multi-objective topology optimization of structures subject to crash and static load cases N. Aulig, S. Menzel, E. Nutwell & D. DetwilerA robust approach to the optimization of structures made of unilateral material M. Bruggi & P. DuysinxOptimal packages: Binding regular polyhedra F. KovácsMS02 – Optimization in oil and gas industriesA multifidelity approach to waterflooding optimization M. Fragoso, B. Horowitz & J. RodriguesMulticriteria solutions for optimum reservoir management S.M.B. Afonso, L.C. Oliveira, J.W.O. Pinto, B. Horowitz & R.B.WillmersdorfA MILP formulation for scheduling oil tankers for offloading operations with variable travel time L.S. de Assis, E. Camponogara & A. PlucenioA modified shuffled frog-leaping algorithm to model products transport in pipeline networks F. Lamboia, L.V.R. de Arruda & F. Neves Jr.A mathematical programming formulation for robust production optimization of gas-lifted oil fields E. Hülse & E. CamponogaraOptimized ballast control in load-out operations M.C.T. Reyes, P. Kaleff, S.G. Ramon & J.R. SarmientoHelicopter routing problem applied to offshore platforms J.I. Soletti, S.H.V. Carvalho, C.J. Sousa &A.M. Oliveira Jr.MS03 – New advances in derivative-free optimization methods for engineering optimizationHybrid multi-criterion optimization strategies for complex technical problems S. KuxGlobal optimization design for expensive computational simulations in aerodynamics using a novel surrogate model approach L. Carro-Calvo, S. Salcedo-Sanz, E. Andrés-Pérez & M.J. Martin-BurgosStructural optimization of a joined wing aircraft using DMS algorithm T. Pires, J.F.A. Madeira &A. SulemanMS04 – Optimization methods in biomechanics and biomedical engineeringA pre-operational study magnification measurement and error estimation of residual tibia kinematics within below knee prosthetics A. Breen, M. Dupac, S. Noroozi & N. OsborneOptimal approach to the human motion reconstruction within the limitation of the kinematic data acquisition procedures C. Quental, J. Folgado, J. Ambrósio & J. MonteiroThe callus formation in bone healing as a shape optimization problem F.O. Ribeiro, P.R. Fernandes, J. Folgado, M.J. Gómez-Benito & J.M. García-AznarA framework for custom design and fabrication of cranio-maxillofacial prostheses using investment casting V. Csáky, R.J. Neto, T.P. Duarte, J. Lino Alves, M. Couto & M. MachadoParametric optimization of coronary stents based on finite element models N.S. Ribeiro, J.O. Folgado & H.C. RodriguesMS05 – Optimization of laminated composite structuresHierarchical optimization of fiber reinforced composites for natural frequencies R.T.L. Ferreira, H.C. Rodrigues & J.M. GuedesOptimal design of composite structures subjected to fatigue loading in a fuzzy environment P. Ke˛dziora &A. MucReducing of the stress concentration near mounting zones of the wind turbine composite blade P.A. Oganesyan, I.V. Zhilyaev, V.S. Shevtsova & J.-K.WuCombined topology and stacking sequence optimization of composite laminated structures for structural performance measures G.P. Rodrigues, J.M. Guedes & J.O. FolgadoViscoelastic material parameter estimation in sandwich structures V.J.S. Carvalho, A.L. Araújo & N.M.M. MaiaA design optimization study of a partially damped sandwich structure S. Naimi, S. Assaf & M.A. HamdiMS06 – Inverse problems in engineeringDirect and optimization methods for the localization of obstacles in a porous media N.F.M. MartinsBayesian estimate of mass fraction of burned fuel in internal combustion engines using pressure measurements D.C. Estumano, F.C. Hamilton, M.J. Colaço, A.J.K. Leiroz, H.R.B. Orlande, R.N. Carvalho & G.S. DulikravichComparison of two inverse strategies to characterise soil profiles D.N.Wilke, S. Kok & G. HeymannEstimating the stress-strain curve of steel wire S. Kok & D.N.WilkeMeshless methods for the inverse problem related to the determination of non-Newtonian fluid properties from the volume flow experiment J.A. Kołodziej, M. Mierzwiczak & J.K. GrabskiDetermination of non-uniformity of unidirectional fibrous porous media as inverse problem J.A. Kolodziej, M. Mierzwiczak & P. FritzkowskiSimultaneous boundary value and material parameter estimation using imperfect compression data G.J. Jansen van Rensburg, S. Kok & D.N.WilkeOn introducing restrictions for mechanism design I. Fernández de Bustos, V. García Marina, R. Ansola & M. AbásoloUsing inverse mapping to directly solve inverse problems E. Asaadi, S. Kok & P.S. HeynsA new aerodynamic inverse method for the design of ducts J.E. BorgesFall detection modeling based on inverse problems I. Figueiredo, S. Kumar, C. Leal & L. PintoAuthor index

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Book SynopsisA series of essays introducing the applications of machine learning and statistics in natural language processing, speech recognition and web search for non-technical readersTrade Review"This volume originates from a series of blog articles by the author, who works as senior staff research scientist for Google China. The blog articles have been rewritten to make them more accessible to uninitiated readers. As a result, the book contains 29 chapters which may be read independently. The aim is to provide evidence for the beauty of mathematics and the wealth of its applications to the layman . . . The volume may be quite valuable for readers who want to get some insight into how enterprises like Google achieve their performance, and how much mathematics is at work in the background of many commonplace services . . . "~Dieter Riebesehl (Lüneburg), zbMathTable of ContentsWords, languages vs. numbers, information. Natural language processing: from rules to statistics. Statistical language models. Chinese, Japanese, and Korean Word segmentation. Hidden Markov models. Measurement and usage of information. Fred Jelinek and modern natural language processing. Beauty of simplicity: Boolean algebra and search engines. Graph theory and web crawlers. PageRank–Google’s democratic ranking algorithm. Determing the relevance of webpages and queries. Finite state machines and dynamic programming: Core technologies of Google local search. Cosine similarity and news classification. Matrix calculation and clustering of text documents. Information fingerprints and their applications. Mathematical principles of cryptography. All that is gold does not glitter: search engine anti-SPAM. The importance of mathematical models. Don’t put all your eggs in one basket: maximum entropy modeling. The principle of (Chinese pinyin) input method editor. Bloom filter. Bayesian networks: Extensions of hidden Markov models. Conditional random field, syntactic parsing, and other applications. Viterbi and his algorithm. God algorithm: Expectation-maximization algorithms. Logistic regression and web search advertisement. Divide and conquer and Google cloud computing fundamentals. Google Brain and neural networks. The power of big data.

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Book SynopsisDuring the last 60 years the discipline of human factors (HF) has evolved alongside progress in engineering, technology, and business. Contemporary HF is clearly shifting towards addressing the human-centered design paradigm for much larger and complex societal systems, the effectiveness of which is affected by recent advances in engineering, science, and education. Human Factors of a Global Society: A System of Systems Perspective explores the future challenges and potential contributions of the human factors discipline in the Conceptual Age of human creativity and social responsibility.Written by a team of experts and pioneers, this book examines the human aspects related to contemporary societal developments in science, engineering, and higher education in the context of unprecedented progress in those areas. It also discusses new paradigms for higher education, including education delivery, and administration from a systems of systems perspective. It then examines Table of ContentsHuman Factors and Technology. Psychology. Management. Higher Education. Education in Modern Society.

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Book SynopsisMany professionals and students in engineering, science, business, and other application fields need to develop Windows-based and web-enabled information systems to store and use data for decision support, without help from professional programmers. However, few books are available to train professionals and students who are not professional programmers to develop these information systems. Developing Windows-Based and Web-Enabled Information Systems fills this gap, providing a self-contained, easy-to-understand, and well-illustrated text that explores current concepts, methods, and software tools for developing Windows-based and web-enabled information systems. Written in an easily accessible style, the book details current concepts, methods, and software tools for Windows-based and web-enabled information systems that store and use data. It is self-contained with easy-to-understand small examples to walk through concepts and implementation details along with large-scTrade Review"This book takes a comprehensive approach to cover the topics of information systems and their development. At the same time it has detailed examples to help readers at different levels. … detailed examples and case studies makes it a good textbook and reference for readers of diverse backgrounds."—Xiangyang Li, Johns Hopkins University"The main strength of this book is that it is written by industrial engineering professors that understand how to present important data management concepts to engineers that may not have a computer science background. Most books on data management and information systems are written with the computing professional in mind. This book finally gives engineers an understandable approach to learning the fundamental data management concepts that are relevant to engineering applications."—Susan D Urban, Texas Tech University"The book is provides a comprehensive introduction to the concepts of information systems. Furthermore, this book has struck the right balance of having sufficient business case concepts for implementing information systems as well as including important technical theories on designing databases."—Eugene Rex L. Jalao, Ph.D., University of the Philippines Diliman"… the most comprehensive book to introduce information system. … covers all the topics related to information system from theoretical background to practical applications. … organized very well and considers the diversity of the readers which will attract a huge number of audiences. … the best textbook for information system related class at both the undergraduate and graduate levels. … covers lots of complex case studies."—Mengqi Hu, Mississippi State UniversityTable of ContentsFoundations of Information Systems. Boolean algebra and digital logic circuits. Digital data representation. Computer system software. Network system software. Information Assurance. An Overview of Information Systems for Window and Web Applications. Database Design and Development. Data Modeling: E-R and EE-R Modeling. Data modeling: Relational Data Modeling and Normalization. SQL. Access. MySQL. Object-Oriented Database. Windows Application Development. Visual Basic Programming I. Visual Basic Programming II. Visual Basic Programming III. Windows Forms and Controls with VBA. Database connectivity with VBA. Windows Forms and Controls with VB.NET. Database connectivity with VB.NET. Web Application Development. Chapter 20. Web applications. Web services. Working with XML I. Working with XML II. Case Studies. A Business Application - Use of VB A and Database. An Engineering Application - Use of VB. NET and Database. A Science Application - Use of ASP.NET and Database.

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Book SynopsisA Concise Handbook of Mathematics, Physics, and Engineering Sciences takes a practical approach to the basic notions, formulas, equations, problems, theorems, methods, and laws that most frequently occur in scientific and engineering applications and university education. The authors pay special attention to issues that many engineers and students find difficult to understand.The first part of the book contains chapters on arithmetic, elementary and analytic geometry, algebra, differential and integral calculus, functions of complex variables, integral transforms, ordinary and partial differential equations, special functions, and probability theory. The second part discusses molecular physics and thermodynamics, electricity and magnetism, oscillations and waves, optics, special relativity, quantum mechanics, atomic and nuclear physics, and elementary particles. The third part covers dimensional analysis and similarity, mechanics of point masses and riTrade ReviewConcise presentation (without proofs), mindfulness of differing mathematical backgrounds (avoidance of special terminology when possible), and emphasis on practical aspects (formulas, problems, methods, and laws that occur frequently in engineering applications) contribute to the usefulness of this single-volume reference. Many sections are self contained; subsections are arranged in increasing order of complexity; and a bibliography is included for each chapter. …—SciTech Book News, February 2011Table of ContentsMathematics. Physics. Elements of Applied and Engineering Sciences. Supplements. Index.

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Book SynopsisThe purpose of this book is to give an exposition of recently adaptive PI/PD/PID control design for nonlinear systems. Since PI/PD/PID control is simple in structure and inexpensive in implementation, it has been undoubtedly the most widely employed controller in industry. In fact, PI/PD/PID controllers are sufficient for many control problems, particularly when process dynamics are benign and the performance requirements are modest. The book focuses on how to design general PI/PD/PID controller with self-tuning gains for different systems, which includes SISO nonlinear system, SISO nonaffine system and MIMO nonlinear system.Table of ContentsIntroduction. Classical PID Control. Adaptive PI Control for SISO Affine Systems. Generalized PI Control for SISO Nonaffine Systems. Adaptive PI Control for MIMO Nonlinear Systems. Adaptive PI Control for Strict Feedback Systems. Adaptive PID Control for MIMO Nonlinear Systems. PD Control Application to High Speed Trains. PID Control Application to Robotic Systems.

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Book SynopsisTrackability and Tracking of General Linear Systems deals with five classes of the systems, three of which are new, begins with the definition of time together with a brief description of its crucial properties and with the principles of the physical uniqueness and continuity of physical variables. They are essential for the natural tracking control synthesis. The book presents further new results on the new compact, simple and elegant calculus that enabled the generalization of the transfer function matrix concept and of the state concept, the completion of the trackability and tracking concepts together with the proofs of the trackability and tracking criteria, as well as the natural tracking control synthesis for all five classes of the systems. Features â Crucially broadens the state space concept and the complex domain fundamentals of the dynamical systems to the control systems. â Addresses the knowledge and ability necessary to study and design control systems that will satisfy the fundamental control goal. â Outlines new effective mathematical means for effective complete analysis and synthesis of the control systems. â Upgrades, completes and essentially generalizes the control theory beyond the existing boundaries. â Provides information necessary to create and teach advanced inherently upgraded control courses.Table of ContentsIntroduction. IO systems. ISO systems. EISO systems. HISO systems. IIO systems. Fundamental control principle. Tracking fundamentals. Trackability fundamentals. Various systems trackability. Linear tracking control (LiTC). Lyapunov Tracking Control (LyTC). Natural Tracking Control (NTC). Appendices: Notation, Equivalent definitions, Example, Proofs, Transformations. Bibliography. Index.

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Book SynopsisOver the last 50 years, the theory and the methods of reliability analysis have developed significantly. Therefore, it is very important to the reliability specialist to be informed of each reliability measure. This book will provide historical developments, current advancements, applications, numerous examples, and many case studies to bring the reader up-to-date with the advancements in this area.It covers reliability engineering in different branches, includes applications to reliability engineering practice, provides numerous examples to illustrate the theoretical results, and offers case studies along with real-world examples.This book is useful to engineering students, research scientist, and practitioners working in the field of reliability.Table of ContentsChapter 1 Preventive Maintenance Modeling: State of the ArtSylwia Werbińska-WojciechowskaChapter 2 Inspection Maintenance Modeling for Technical Systems:An OverviewSylwia Werbińska-WojciechowskaChapter 3 Application of Stochastic Processes in Degradation Modeling:An OverviewShah Limon, Ameneh Forouzandeh Shahraki,and Om Prakash YadavChapter 4 Building a Semi-automatic Design for Reliability Survey withSemantic Pattern RecognitionChristian Spreafico and Davide RussoChapter 5 Markov Chains and Stochastic Petri Nets for Availability andReliability ModelingPaulo Romero Martins Maciel, Jamilson Ramalho Dantas,and Rubens de Souza Matos JúniorChapter 6 An Overview of Fault Tree Analysis and Its Application in DualPurposed Cask Reliability in an Accident ScenarioMaritza Rodriguez Gual, Rogerio Pimenta Morão, LuizLeite da Silva, Edson Ribeiro, Claudio Cunha Lopes,and Vagner de OliveiraChapter 7 An Overview on Failure Rates in Maintenance PoliciesXufeng Zhao and Toshio NakagawaChapter 8 Accelerated Life Tests with Competing Failure Modes:An OverviewKanchan Jain and Preeti Wanti SrivastavaChapter 9 European Reliability StandardsMiguel Angel Navas, Carlos Sancho, and Jose CarpioChapter 10 Time-Variant Reliability Analysis Methods for DynamicStructuresZhonglai Wang and Shui YuChapter 11 Latent Variable Models in ReliabilityLaurent BordesChapter 12 Expanded Failure Modes and Effects Analysis: A DifferentApproach for System Reliability Assessment Perdomo Ojeda Manuel, Rivero Oliva Jesús, and SalomónLlanes JesúsChapter 13 Reliability Assessment and Probabilistic Data Analysis ofVehicle Components and Systems Zhigang WeiChapter 14 Maintenance Policy Analysis of a Marine Power GeneratingMulti-state System Thomas Markopoulos and Agapios N. PlatisChapter 15 Vulnerability Discovery and Patch Modeling: State of the Art Avinash K. Shrivastava, P. K. Kapur, and Misbah AnjumChapter 16 Signature Reliability Evaluations: An Overview of DifferentSystems Akshay Kumar, Mangey Ram, and S. B. Singh

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Book SynopsisSHORTLISTED FOR THE FINANCIAL TIMES & MCKINSEY 2020 BUSINESS BOOK OF THE YEAROne of Fortune Best Books of the YearOne of Inc. Best Business Books of the YearOne of The Times (UK) Best Business Books of the YearA New York Times Book Review Editors' ChoiceFrom an Oxford economist, a visionary account of how technology will transform the world of work, and what we should do about it From mechanical looms to the combustion engine to the first computers, new technologies have always provoked panic about workers being replaced by machines. For centuries, such fears have been misplaced, and many economists maintain that they remain so today. But as Daniel Susskind demonstrates, this time really is different. Breakthroughs in artificial intelligence mean that all kinds of jobs are increasingly at risk. Drawing on almost a decade of research in the field, Susskind argues that

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Book SynopsisComprehensive guide on learning automata, introducing two variants to accelerate convergence and computational update speed Learning Automata and Their Applications to Intelligent Systems provides a comprehensive guide on learning automata from the perspective of principles, algorithms, improvement directions, and applications. The text introduces two variants to accelerate the convergence speed and computational update speed, respectively; these two examples demonstrate how to design new learning automata for a specific field from the aspect of algorithm design to give full play to the advantage of learning automata. As noisy optimization problems exist widely in various intelligent systems, this book elaborates on how to employ learning automata to solve noisy optimization problems from the perspective of algorithm design and application. The existing and most representative applications of learning automata include classification, clustering, game, knapsack, network, optimization, r

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Book SynopsisAt publication, The Control Handbook immediately became the definitive resource that engineers working with modern control systems required. Among its many accolades, that first edition was cited by the AAP as the Best Engineering Handbook of 1996. Now, 15 years later, William Levine has once again compiled the most comprehensive and authoritative resource on control engineering. He has fully reorganized the text to reflect the technical advances achieved since the last edition and has expanded its contents to include the multidisciplinary perspective that is making control engineering a critical component in so many fields. Now expanded from one to three volumes, The Control Handbook, Second Edition organizes cutting-edge contributions from more than 200 leading experts. The third volume, Control System Advanced Methods, includes design and analysis methods for MIMO linear and LTI systems, Kalman filters and observerTable of ContentsAnalysis Methods for MIMO Linear Systems: Numerical and Computational Issues in Linear Control and System Theory. Multivariable Poles, Zeros, and Pole-Zero Cancellations. Fundamentals of Linear Time-Varying Systems. Balanced Realizations, Model Order Reduction, and the Hankel Operator. Geometric Theory of Linear Systems. Polynomial and Matrix Fraction Descriptions. Robustness Analysis with Real Parametric Uncertainty. MIMO Frequency Response Analysis and the Singular Value Decomposition. Stability Robustness to Unstructured Uncertainty for Linear Time Invariant Systems. Trade-Offs and Limitations in Feedback Systems. Modeling Deterministic Uncertainty. Kalman Filter and Observers: Linear Systems and White Noise. Kalman Filtering. Riccati Equations and their Solution. Observers. Design Methods for MIMO LTI Systems: Eigenstructure Assignment. Linear Quadratic Regulator Control. H2 (LQG) and H∞ Control. l1 Robust Control: Theory, Computation, and Design. The Structured Singular Value (μ) Framework. Algebraic Design Methods. Quantitative Feedback Theory (QFT) Technique. Robust Servomechanism Problem. Linear Matrix Inequalities in Control. Optimal Control. Decentralized Control. Decoupling. Linear Model Predictive Control in the Process Industries. Analysis and Design of Hybrid Systems: Computation of Reach Sets for Dynamical Systems. Hybrid Dynamical Systems: Stability and Stabilization. Optimal Control of Switching Systems via Embedding into Continuous Optimal Control Problem. Adaptive Control: Automatic Tuning of PID Controllers. Self-Tuning Control. Model Reference Adaptive Control. Robust Adaptive Control. Iterative Learning Control. Analysis and Design of Nonlinear Systems: Nonlinear Zero Dynamics. The Lie Bracket and Control. Two Timescale and Averaging Methods. Volterra and Fliess Series Expansions for Nonlinear Systems. Integral Quadratic Constraints. Control of Nonholonomic and Underactuated Systems. Stability: Lyapunov Stability. Input-Output Stability. Input-to-State Stability. Design. Feedback Linearization of Nonlinear Systems. The Steady-State Behavior of a Nonlinear System. Nonlinear Output Regulation. Lyapunov Design, Variable Structure, Sliding-Mode Controller Design. Control of Bifurcations and Chaos, Eyad H. Abed. Open-Loop Control Using Oscillatory Inputs. Adaptive Nonlinear Control, Intelligent Control. Fuzzy Control. Neural Control. System Identification: System Identification. Stochastic Control: Discrete Time Markov Processes. Stochastic Differential Equations. Linear Stochastic Input–Output Models. Dynamic Programming. Approximate Dynamic Programming. Stability of Stochastic Systems. Continuous-Time Linear Systems. Probabilistic and Randomized Tools for Control Design. Stabilization of Stochastic Nonlinear Continuous-Time Systems. Control of Distributed Parameter Systems: Control of Systems Governed by Partial Differential Equations. Controllability of Thin Elastic Beams and Plates. Control of the Heat Equation. Observability of Linear Distributed-Parameter Systems. Boundary Control of PDE’s: . Stabilization of Fluid Flows. Networks and Networked Controls: Control Over Digital Networks. Decentralized Control and Algebraic Approaches. Estimation and Control across Analog Erasure Channels. Passivity Approach to Network Stability Analysis and Distributed Control Synthesis. Index.

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Book SynopsisBased on research projects supported by the National Natural Science Foundation of China and Nanjing University of Aeronautics and Astronautics, Optimization of Regional Industrial Structures and Applications provides an authoritative introduction to and survey of the cutting-edge research and applications in industrial structure optimization. Employing grey systems theory as its method of analysis, it integrates grey systems theory with industrial structure optimization theory to provide dynamic and efficient methods of measurement, analysis, and decision making. The authors cover several models of grey regional industrial structure, including grey correlation priority analysis, industrial structure order degree measurement model, regional leading industries grey assessment model and turnpike model. The first part of the book clarifies basic theory. This section covers the production and development of industrial structure theory, evolution laws of inTable of ContentsThe Forming and Development of Industrial Structure Theory. Industrial Strucutre’s Evolving Track and Law. The Key Influence Factors of Industrial Structure’s Upgrading. The Rationalization of Industrial Structure. The Heightening of Industrial Structure. The In-Output Analysis of Industrial Structure. Regional Industrial Structure. Choosing Regional Leading Industry. The Mathematics Models of Regional Industrial Structure’s Optimzing. The Research on Ma-an-Shan City’s Industrial Structure’s Optimization and Upgrading in "the 11th Five-Year Plan". The Emphasis, Ideas, and Strategy of Jiang Su Province’s Industrial Structure Adjustment. The Approach and Countermeasures of Achieving the Heightening of Industrial Structure in Jiang Su Province. The Approach and Countermeasures of the Heightening of Industrial Structure During "the 11th Five-Year Plan".

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Book SynopsisA book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely. Outlining a wide range of methods and models, it begins by examining the method of qualitative assessment. Next, it describes the process and methods for building an index system of evaluation and considers the compared evaluation and the logical framework approach, analytic hierarchy process (AHP), and the data envelopment analysis (DEA) relative efficiency evaluation method.Unique in its emphasis on the practical applications of systems evaluation methods and models, the book introduces several new evaluation models of grey system, including general grey incidence model, grey incidence models based on similarity and closeness, grey cluster evaluation based on triangular whitenization functions, and multi-attribute grey target decision modeTable of ContentsIntroduction 1 Common System Evaluation Methods and Models 2 Grey System Evaluation Models 3 Postevaluation of Road–Bridge Construction: Case Study of Lianxu Highway in China 4 Efficiency Evaluations of Scientific and Technological Activities 5 Evaluation of Energy Saving in China 6 International Cooperation Project Selection

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Book SynopsisFuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. These three types of sets and their various hybridizations provide powerful frameworks for image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, Rough Fuzzy Image Analysis: Foundations and Methodologies introduces the fundamentals and applications in the state of the art of rough fuzzy image analysis. In the first chapter, the distinguished editors explain how fuzzy, near, and rough sets provide the basis for the stages of pictorial pattern recognition: image transformation, feature extraction, and classification. The text then discusses hybrid approaches that combine fuzzy sets and rough sets in image analysis, illustrates how to perform image analysis using only rough sets, and describes tolerance spaces and a perceptual systems approach to image analysis. It also presents a Table of ContentsCantor, Fuzzy, Near, and Rough Sets in Image Analysis. Rough Fuzzy Clustering Algorithm for Segmentation of Brain MR Images. Image Thresholding Using Generalized Rough Sets. Mathematical Morphology and Rough Sets. Rough Hybrid Scheme: An Application of Breast Cancer Imaging. Applications of Fuzzy Rule-Based Systems in Medical Image Understanding. Near Set Evaluation and Recognition (NEAR) System. Perceptual Systems Approach to Measuring Image Resemblance. From Tolerance Near Sets to Perceptual Image Analysis. Image Segmentation: A Rough-Set Theoretic Approach. Rough Fuzzy Measures in Image Segmentation and Analysis. Discovering Image Similarities: Tolerance Near Set Approach.

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Book SynopsisPart I: Visions and Overviews.- Future Directions in Robotic Surgery.- Military Robotic Combat Casualty Extraction and Care.- Telemedicine for the Battlefield: Present and Future Technologies.- Overcoming Barriers to Wider Adoption of Mobile Telerobotic Surgery: Engineering, Clinical and Business Challenges.- Part II: Systems.- Accurate Positioning for Intervention on the Beating Heart using a Crawling Robot.- Miniature In Vivo Robots for NOTES.- A Compact, Simple, and Robust Teleoperated Robotic Surgery System.- Raven - Optimization of a Surgical Robot and Experiments in Telesurgery.- The da Vinci Surgical System.- RIO: Robotic-Arm Interactive Orthopedic System MAKOplasty User Interactive Haptic Orthopedic Robotics.- Robotic Surgery: Enabling Technology. Enabling Medical Robotics for the Next Generation of Minimally Invasive Procedures: Minimally Invasive Cardiac Surgery with Single Port Access.- Wireless Intraocular Microrobots: Opportunities and Challenges.- Single and Multiple RobTrade ReviewFrom the reviews:“This book is great collection and well arranged. … the study results within this book is very useful for clinical surgeon. … every surgical department in any hospital should got this book.” (Amazon.com, May, 2011)Table of ContentsPart I: Visions and Overviews.- Future Directions in Robotic Surgery.- Military Robotic Combat Casualty Extraction and Care.- Telemedicine for the Battlefield: Present and Future Technologies.- Overcoming Barriers to Wider Adoption of Mobile Telerobotic Surgery: Engineering, Clinical and Business Challenges.- Part II: Systems.- Accurate Positioning for Intervention on the Beating Heart using a Crawling Robot.- Miniature In Vivo Robots for NOTES.- A Compact, Simple, and Robust Teleoperated Robotic Surgery System.- Raven - Optimization of a Surgical Robot and Experiments in Telesurgery.- The da Vinci Surgical System.- RIO: Robotic-Arm Interactive Orthopedic System MAKOplasty – User Interactive Haptic Orthopedic Robotics.- Robotic Surgery: Enabling Technology. Enabling Medical Robotics for the Next Generation of Minimally Invasive Procedures: Minimally Invasive Cardiac Surgery with Single Port Access.- Wireless Intraocular Microrobots: Opportunities and Challenges.- Single and Multiple Robotic Capsules for Endoluminal Diagnosis and Surgery.- Visual Guidance of an Active Handheld Microsurgical Tool.- Swimming Micro Robots for Medical Applications.- Flagellated Bacterial Nanorobots for Medical Interventions in the Human Body.- Part III: Engineering Developments.- Force Feedback and Sensory Substitution for Robot-Assisted Surgery.- Tactile Feedback in Surgical Robotics.- Robotic Techniques for Minimally Invasive Tumor Localization.- Motion Prediction and 3D Tracking of the Beating Heart.-Towards the Development of a Robotic System for Beating Heart Surgery.- Robotic Needle Steering: Design, Modeling, Planning, and Image Guidance.- Macro and Micro Soft-tissue Biomechanics and Tissue Damage.- Objective Assessment of Surgical Skills.- Part IV: Clinical Applications / Overviews.- Telesurgery – Translation Technology to Clinical Practice.- History of Robots in Orthopedics.- Robotic-Assisted Urologic Applications.- Applications of Surgical Robotics in Cardiac Surgery.- Robotics in Neurosurgery.- Applications of Surgical Robotics in Pediatric Surgery.

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Book Synopsis1 Introduction to the Monograph.- 1.1 Background and Motivation: Transient Response Control.- 1.2 Organization of the Monograph.- 2 Iterative Learning Control: An Overview.- 2.1 Introduction.- 2.2 Literature Review.- 2.3 Problem Formulation.- 3 Linear Time-Invariant Learning Control.- 3.1 Convergence with Zero Error.- 3.2 Convergence with Non-Zero Error.- 3.3 The Nature of the Solution.- 4 LTI Learning Control via Parameter Estimation.- 4.1 System Description.- 4.2 Main Result.- 4.3 Comments.- 5 Finite-Horizon Learning Control.- 5.1 l?-Optimal Learning Control with Memory.- 5.2 Learning Convergence in One Step.- 5.3 Learning Control with Multirate Sampling.- 5.4 Examples.- 5.5 Comments and Extensions.- 6 Nonlinear Learning Control.- 6.1 Learning Control for Nonlinear Systems.- 6.2 Learning Controller for a Class of Nonlinear Systems.- 7 Artificial Neural Networks for Iterative Learning Control.- 7.1 Neural Network Controllers.- 7.2 Static Learning Controller Using an ANN.- 7.3 Dynamical Learning Controller Using an ANN.- 7.4 Reinforcement Learning Controller Using an ANN.- 8 Conclusion.- 8.1 Summary.- 8.2 Directions for Future Research.- Appendix A: Some Basic Results on Multirate Sampling.- A.1 Introduction.- A.3 Basic Result.- Appendix B: Tutorial on Artificial Neural Networks.- B.1 An Introduction to Neural Networks.- B.1.1 Neurons.- B.1.2 Interconnection Topology.- B.1.3 Learning Laws.- B.2 Historical Background.- B.3 Properties of Neural Networks.- B.3.1 Pattern Classification and Associative Memory.- B.3.2 Self-Organization and Feature Extraction.- B.3.3 Optimization.- B.3.4 Nonlinear Mappings.- B.4 Neural Nets and Computers.- B.5 Derivation of Backpropagation.- B.6 Neural Network References.- References.Table of Contents1 Introduction to the Monograph.- 1.1 Background and Motivation: Transient Response Control.- 1.2 Organization of the Monograph.- 2 Iterative Learning Control: An Overview.- 2.1 Introduction.- 2.2 Literature Review.- 2.3 Problem Formulation.- 3 Linear Time-Invariant Learning Control.- 3.1 Convergence with Zero Error.- 3.2 Convergence with Non-Zero Error.- 3.3 The Nature of the Solution.- 4 LTI Learning Control via Parameter Estimation.- 4.1 System Description.- 4.1.1 Notation.- 4.1.2 Parameter Estimator and Learning Control Law.- 4.2 Main Result.- 4.3 Comments.- 5 Finite-Horizon Learning Control.- 5.1 l?-Optimal Learning Control with Memory.- 5.2 Learning Convergence in One Step.- 5.3 Learning Control with Multirate Sampling.- 5.4 Examples.- 5.4.1 DC-Motor.- 5.4.2 Non-Minimum Phase System.- 5.5 Comments and Extensions.- 6 Nonlinear Learning Control.- 6.1 Learning Control for Nonlinear Systems.- 6.2 Learning Controller for a Class of Nonlinear Systems.- 6.2.1 Preliminaries.- 6.2.2 Adaptive Gain Adjustment.- 6.2.3 Simulation Experiment.- 7 Artificial Neural Networks for Iterative Learning Control.- 7.1 Neural Network Controllers.- 7.2 Static Learning Controller Using an ANN.- 7.3 Dynamical Learning Controller Using an ANN.- 7.4 Reinforcement Learning Controller Using an ANN.- 7.4.1 Reinforcement Learning.- 7.4.2 Proposed Learning Control System.- 7.4.3 Example and Comments.- 8 Conclusion.- 8.1 Summary.- 8.2 Directions for Future Research.- Appendix A: Some Basic Results on Multirate Sampling.- A.1 Introduction.- A.3 Basic Result.- Appendix B: Tutorial on Artificial Neural Networks.- B.1 An Introduction to Neural Networks.- B.1.1 Neurons.- B.1.2 Interconnection Topology.- B.1.3 Learning Laws.- B.2 Historical Background.- B.3 Properties of Neural Networks.- B.3.1 Pattern Classification and Associative Memory.- B.3.2 Self-Organization and Feature Extraction.- B.3.3 Optimization.- B.3.4 Nonlinear Mappings.- B.4 Neural Nets and Computers.- B.5 Derivation of Backpropagation.- B.6 Neural Network References.- References.

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Book Synopsis1 Introduction to Model Based Predictive Control.- 1.1 MPC Strategy.- 1.2 Historical Perspective.- 1.3 Outline of the chapters.- 2 Model Based Predictive Controllers.- 2.1 MPC Elements.- 2.2 Review of some MPC Algorithms.- 2.3 MPC Based on the Impulse Response.- 2.4 Generalized Predictive Control.- 2.5 Constrained Receding-Horizon Predictive Control.- 2.6 Stable GPC.- 2.7 Filter Polynomials for Improving Robustness.- 3 Simple Implementation of GPC for Industrial Processes.- 3.1 Plant Model.- 3.2 The Dead Time Multiple of Sampling Time Case.- 3.3 The Dead Time non Multiple of the Sampling Time Case.- 3.4 Integrating Processes.- 3.5 Consideration of Ramp Setpoints.- 4 Robustness Analysis in Precomputed GPC.- 4.1 Structured Uncertainties.- 4.2 Stability Limits with Structured Uncertainties.- 4.3 Unstructured Uncertainties.- 4.4 Relationship between the two Types of Uncertainties.- 4.5 General Comments.- 5 Multivariate GPC.- 5.1 Derivation of Multivariable GPC.- 5.2 Obtaining a Matrix FracTable of Contents1 Introduction to Model Based Predictive Control.- 1.1 MPC Strategy.- 1.2 Historical Perspective.- 1.3 Outline of the chapters.- 2 Model Based Predictive Controllers.- 2.1 MPC Elements.- 2.1.1 Prediction Model.- 2.1.2 Objective Function.- 2.1.3 Obtaining the Control Law.- 2.2 Review of some MPC Algorithms.- 2.3 MPC Based on the Impulse Response.- 2.3.1 Process Model and Prediction.- 2.3.2 Control Law.- 2.4 Generalized Predictive Control.- 2.4.1 Formulation of Generalized Predictive Control.- 2.4.2 The Coloured Noise Case.- 2.4.3 An example.- 2.5 Constrained Receding-Horizon Predictive Control.- 2.5.1 Computation of the Control Law.- 2.5.2 Properties.- 2.6 Stable GPC.- 2.6.1 Formulation of the control law.- 2.7 Filter Polynomials for Improving Robustness.- 2.7.1 Selection of the T polynomial.- 2.7.2 Relation with other Formulations.- 3 Simple Implementation of GPC for Industrial Processes.- 3.1 Plant Model.- 3.1.1 Plant Identification: The Reaction Curve Method.- 3.2 The Dead Time Multiple of Sampling Time Case.- 3.2.1 Discrete Plant Model.- 3.2.2 Problem Formulation.- 3.2.3 Computation of the Controller Parameters.- 3.2.4 Role of the Control-Weighting Factor.- 3.2.5 Implementation Algorithm.- 3.2.6 An Implementation Example.- 3.3 The Dead Time non Multiple of the Sampling Time Case.- 3.3.1 Discrete Model of the Plant.- 3.3.2 Controller Parameters.- 3.3.3 Example.- 3.4 Integrating Processes.- 3.4.1 Derivation of the Control Law.- 3.4.2 Controller parameters.- 3.4.3 Example.- 3.5 Consideration of Ramp Setpoints.- 3.5.1 Example.- 4 Robustness Analysis in Precomputed GPC.- 4.1 Structured Uncertainties.- 4.1.1 Parametric Uncertainties.- 4.1.2 Unmodelled Dynamics.- 4.1.3 Both Types of Uncertainties.- 4.2 Stability Limits with Structured Uncertainties.- 4.2.1 Influence of Parametric Uncertainties.- 4.2.2 Influence of Unmodelled Dynamics.- 4.2.3 Combined Effect.- 4.2.4 Influence of the Control Effort.- 4.3 Unstructured Uncertainties.- 4.3.1 Process Description.- 4.3.2 Measurement of the Robustness of the GPC.- 4.3.3 Robustness Limits.- 4.4 Relationship between the two Types of Uncertainties.- 4.4.1 Uncertainty in the Gain.- 4.4.2 Uncertainty in the Delay.- 4.5 General Comments.- 5 Multivariate GPC.- 5.1 Derivation of Multivariable GPC.- 5.1.1 White Noise Case.- 5.1.2 Coloured noise case.- 5.2 Obtaining a Matrix Fraction Description.- 5.2.1 Transfer Matrix Representation.- 5.2.2 Parametric Identification.- 5.3 State Space Formulation.- 5.3.1 Matrix Fraction and State Space Equivalences.- 5.4 Dead Time Problems.- 5.5 Example: Distillation Column.- 6 Constrained MPC.- 6.1 Constraints and GPC.- 6.1.1 Illustrative Examples.- 6.2 Revision of Main Quadratic Programming Algorithms.- 6.2.1 The Active Set Methods.- 6.2.2 Feasible Directions Methods.- 6.2.3 Initial Feasible Point.- 6.2.4 Pivoting Methods.- 6.3 Constraints Handling.- 6.3.1 Slew Rate Constraints.- 6.3.2 Amplitude Constraints.- 6.3.3 Output Constraints.- 6.3.4 Constraints Reduction.- 6.4 1-norm.- 6.5 Constrained MPC and Stability.- 7 Robust MPC.- 7.1 Process Models and Uncertainties.- 7.1.1 Truncated Impulse Response Uncertainties.- 7.1.2 Matrix Fraction Description Uncertainties.- 7.1.3 Global Uncertainties.- 7.2 Objective Functions.- 7.2.1 Quadratic Norm.- 7.2.2 ? — ? norm.- 7.2.3 1-norm.- 7.3 Illustrative Examples.- 7.3.1 Bounds on the Output.- 7.3.2 Uncertainties in the Gain.- 8 Applications.- 8.1 Solar Power Plant.- 8.1.1 Control Strategy.- 8.1.2 Plant Results.- 8.2 Composition Control in an Evaporator.- 8.2.1 Description of the Process.- 8.2.2 Obtaining the Linear Model.- 8.2.3 Controller Design.- 8.2.4 Results.- 8.3 Pilot Plant.- 8.3.1 Plant Description.- 8.3.2 Plant Control.- 8.3.3 Flow Control.- 8.3.4 Temperature Control at the Exchanger Output.- 8.3.5 Temperature Control in the Tank.- 8.3.6 Level Control.- 8.3.7 Remarks.- A Revision of the Simplex method.- A.1 Equality Constraints.- A.2 Finding an Initial Solution.- A.3 Inequality Constraints.- B Model Predictive Control Simulation Program.- References.

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Book SynopsisDynamics and Control of Mechanical Systems in Offshore Engineering is a comprehensive treatment of marine mechanical systems (MMS) involved in processes of great importance such as oil drilling and mineral recovery. Ranging from nonlinear dynamic modeling and stability analysis of flexible riser systems, through advanced control design for an installation system with a single rigid payload attached by thrusters, to robust adaptive control for mooring systems, it is an authoritative reference on the dynamics and control of MMS. Readers will gain not only a complete picture of MMS at the system level, but also a better understanding of the technical considerations involved and solutions to problems that commonly arise from dealing with them. The text provides: a complete framework of dynamical analysis and control design for mariTable of ContentsPreliminaries.- Dynamic Load Positioning.- Coupled Nonlinear Flexible Marine Riser.- Flexible Marine Riser with Vessel Dynamics.- Riser System with a Torque Actuator.- Marine Installation System.- Riser Installation System.- Mooring System.

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Book SynopsisThis companion book to MakerShed's Ultimate Arduino Microcontroller Pack provides 26 clearly explained projects that you can build with this top-selling kit right away--including multicolor flashing lights, timers, tools for testing circuits, sound effects, motor control, and sensor devices.

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Book SynopsisHow can you take advantage of feedback control for enterprise programming? With this book, author Philipp K. Janert demonstrates how the same principles that govern cruise control in your car also apply to data center management and other enterprise systems.

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Book SynopsisWritten by one of the authors of Adafruit's Trinket documentation, Getting Started with Trinket gets you up and running quickly with this board, and gives you some great projects to inspire your own creations

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Book SynopsisMaker Pro is a book of essays by more than a dozen prominent and up-and-coming professional makers (Maker Pros). Each essay includes advice and stories on topics such as starting a kit-making business, taking a hardware project open-source, and plenty of encouragement to "quit your day job."

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