Description
Book SynopsisFor dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.
Optimal Measurement Methods for Distributed Parameter System Identification discusses the characteristic features of the sensor placement problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, culminating in the most comprehensive and timely treatment of the issue available. By presenting a step-by-step guide to theoretical aspects and to practical design methods, this book provides a sound understanding of sensor location techniques.
Both researchers and practitioners will find the case studies, the proposed algorithms, and the numerical examples to be invaluable. This text also offers
Table of ContentsPreface, 1 Introduction, 2 Key ideas of identification and experimental design, 3 Locally optimal designs for stationary sensors, 4 Locally optimal strategies for scanning and moving observations, 5 Measurement strategies with alternative design objectives, 6 Robust designs for sensor location, 7 Towards even more challenging problems, 8 Applications from engineering, Appendices, References, Index
