Citation
(1999), "Advances in Industrial Control: Adaptive Internal Model Control", Industrial Robot, Vol. 26 No. 3. https://doi.org/10.1108/ir.1999.04926cae.002
Publisher
:Emerald Group Publishing Limited
Copyright © 1999, MCB UP Limited
Advances in Industrial Control: Adaptive Internal Model Control
Advances in Industrial Control: Adaptive Internal Model Control
A. DattaSpringer1998151 pp.ISBN 3-540-76252-3£37.50 Hardcover
Aimed at practising engineers, researchers and graduate students involved or interested in control engineering, this book is a useful source of information on Adaptive Internal Model Control (AIMC). AIMC is a methodology for the design and analysis of adaptive internal model control schemes, with provable guarantees of stability and robustness.
The eight chapters provide a theoretical basis for analytically justifying some of the reported industrial successes of existing AIMC schemes and brings the latest theoretical advances in the design of robust adaptive systems to the realm of industrial applications.
Chapter 1 is an introductory chapter, addressing model predictive control, internal model control and internal model control in the presence of uncertainty. Chapter 2 covers the fundamental mathematics, with the basic definitions, input-output stability and Lyapunov stability. Internal model control schemes are comprehensively discussed in chapter 3, including the YJBK (Youla-Jabr-Bongiorno-Kucera) parametrization, model reference control, H2 and Hƒ optimal control and robustness to modelling errors. Chapters 4 and 5 discuss on-line parameter estimation and adaptive internal model control schemes, respectively. Chapter 6 covers robust parameter estimation and robust adaptive laws, with the stability and design of robust AIMC schemes, including examples, being covered in chapter 7. Chapter 8 is the concluding chapter.
Appendix A describes the YJBK parametrization of all stabilising controllers and Appendix B discusses optimisation using the gradient method.
Providing that the reader has a reasonable understanding of the mathematics involved with control engineering, this book is both easy to read and a useful guide to adaptive internal model control.