Robust Systems Theory and Applications (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)

A complete, up-to-date textbook on an increasingly importantsubject

Robust Systems Theory and Applications covers both the techniquesused in linear robust control analysis/synthesis and in robust(control-oriented) identification. The main analysis and designmethods are complemented by elaborated examples and a group ofworked-out applications that stress specific practical issues:nonlinearities, robustness against changes in operating conditions,uncertain infinite dimensional plants, and actuator and sensorlimitations. Designed expressly as a textbook for master's andfirst-year PhD students, this volume:
* Introduces basic robustness concepts in the context of SISOsystems described by Laplace transforms, establishing connectionswith well-known classical control techniques
* Presents the internal stabilization problem from two differentpoints of view: algebraic and state --space
* Introduces the four basic problems in robust control and the Loopshaping design method Presents the optimal *2 control problem froma different viewpoint, including an analysis of the robustnessproperties of *2 controllers and a treatment of the generalized *2problem
* Presents the *2 control problem using both the state-spaceapproach developed in the late 1980s and a Linear Matrix Inequalityapproach (developed in the mid 1990s) that encompasses more generalproblems
* Discusses more general types of uncertainties (parametric andmixed type) and ??-synthesis as a design tool
* Presents an overview of optimal ,1 control theory and covers thefundamentals of its star-norm approximation
* Presents the basic tools of model order reduction
* Provides a tutorial on robust identification
* Offers numerous end-of-chapter problems and worked-out examplesof robust control