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Other titles in the Adaptive and Learning Systems for Signal Processing, Communications and Control series:
Nonlinear and Adaptive Control Design (Adaptive and Learning Systems for Signal Processing, Communications and Control)by Miroslav Krstic
Synopses & Reviews
An introduction to a new design for nonlinear control systems--backstepping--written by its own architects.
This innovative book breaks new ground in nonlinear and adaptive control design for systems with uncertainties. Introducing the recursive backstepping methodology, it shows--for the first time--how uncertain systems with severe nonlinearities can be successfully controlled with this new powerful design tool.
Communicative and accessible at a level not usually present in research texts, Nonlinear and Adaptive Control Design can be used as either a stand-alone or a supplemental text in courses on nonlinear or adaptive control, as well as in control research and applications. It eases the reader into the subject matter, assuming only standard undergraduate knowledge of control theory, and provides a pedagogical presentation of the material, most of which is completely new and not available in other textbooks. Written by the creators of backstepping, the book:
* Introduces the basic design tools and demonstrates their effectiveness through worked examples
* Provides detailed proofs and application examples (active suspension, jet engine, induction motor, and many others)
* Develops adaptive backstepping, tuning functions, and modular designs with full state feedback
* Generalizes the methodology to nonlinear systems with output feedback
* Describes the advantages of the new adaptive nonlinear techniques over traditional methods
* Offers a systematic methodology for performance improvement
* Provides new designs for linear systems which can be used independently from therest of the book
* Is self-contained with an extensive summary of stability and passivity prerequisites
* Includes sixty illustrations and tables with design algorithms
Nonlinear and Adaptive Control Design is an absolute must for researchers and graduate students with an interest in nonlinear systems, adaptive control, stability and differential equations and for anyone who would like to find out about the new and exciting advances in these areas.
Book News Annotation:
Written for an audience with a standard undergraduate background in control theory and a basic knowledge of stability concepts. Focuses on designs for systems with uncertainties and introduces the recursive backstepping methodology for controlling uncertain systems with severe nonlinearities. Provides detailed proofs and examples on subjects including nonlinear stabilization, adaptive backstepping, adaptive Lyapunov design, estimation-based design, and control of linear systems. For use as a stand-alone or supplemental text.
Annotation c. Book News, Inc., Portland, OR (booknews.com)
Using a pedagogical style along with detailed proofs and illustrative examples, this book opens a view to the largely unexplored area of nonlinear systems with uncertainties. The focus is on adaptive nonlinear control results introduced with the new recursive design methodology--adaptive backstepping. Describes basic tools for nonadaptive backstepping design with state and output feedbacks.
Includes bibliographical references (p. 541-557) and index.
About the Author
MIROSLAV KRST?C received his PhD from the University of California, Santa Barbara, in 1994 where he is currently a researcher in the Department of Electrical and Computer Engineering.
IOANNIS KANELLAKOPOULOS received his PhD in electrical engineering from the University of Illinois in 1992 and is presently an assistant professor in the Department of Electrical Engineering at the University of California, Los Angeles.
PETAR KOKOTOVI has been Co-Director of the Center for Control Engineering and Computation at the University of California, Santa Barbara, since 1991. Previously, he was with the University of Illinois, where he held the Grainger Chair. His recognition as a leading authority in control theory includes the triennial Quazza Medal by IFAC in 1990 and the 1995 IEEE Control Systems Award.
Table of Contents
Design Tools for Stabilization.
Adaptive Backstepping Design.
Tuning Functions Design.
Modular Design with Passive Identifiers.
Modular Design with Swapping Identifiers.
Output-Feedback Design Tools.
Tuning Functions Designs.
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