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 important subject

Robust Systems Theory and Applications covers both the techniques used in linear robust control analysis/synthesis and in robust (control-oriented) identification. The main analysis and design methods are complemented by elaborated examples and a group of worked-out applications that stress specific practical issues: nonlinearities, robustness against changes in operating conditions, uncertain infinite dimensional plants, and actuator and sensor limitations. Designed expressly as a textbook for master's and first-year PhD students, this volume:
* Introduces basic robustness concepts in the context of SISO systems described by Laplace transforms, establishing connections with well-known classical control techniques
* Presents the internal stabilization problem from two different points of view: algebraic and state --space
* Introduces the four basic problems in robust control and the Loop shaping design method Presents the optimal *2 control problem from a different viewpoint, including an analysis of the robustness properties of *2 controllers and a treatment of the generalized *2 problem
* Presents the *2 control problem using both the state-space approach developed in the late 1980s and a Linear Matrix Inequality approach (developed in the mid 1990s) that encompasses more general problems
* Discusses more general types of uncertainties (parametric and mixed type) and ??-synthesis as a design tool
* Presents an overview of optimal ,1 control theory and covers the fundamentals 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 examples of robust control