Feedback Systems Input Output Properties By C A Desoer Und M Vidyasagar

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Feedback Systems: Input-output Properties

Feedback Systems: Input-output Properties deals with the basic input-output properties of feedback systems. Emphasis is placed on multiinput-multioutput feedback systems made of distributed subsystems, particularly continuous-time systems. Topics range from memoryless nonlinearities to linear systems, the small gain theorem, and passivity. Norms and general theorems are also considered. This book is comprised of six chapters and begins with an overview of a few simple facts about feedback systems and simple examples of nonlinear systems that illustrate the important distinction between the questions of existence, uniqueness, continuous dependence, and boundedness with respect to bounded input and output. The next chapter describes a number of useful properties of norms and induced norms and of normed spaces. Several theorems are then presented, along with the main results concerning linear systems. These results are used to illustrate the applications of the small gain theorem to different classes of systems. The final chapter outlines the framework necessary to discuss passivity and demonstrate the applications of the passivity theorem. This monograph will be a useful resource for mathematically inclined engineers interested in feedback systems, as well as undergraduate engineering students.
Iterative Identification and Control

Author: Pedro Albertos
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models is the main goal of this book. The combination of both subjects into a cohesive development allows the consistent treatment of both problems to yield powerful new tools for the improvement of system performance. Central among the themes of this work is the observation that operation of a system in feedback with a controller exposes the areas in which the model fit is constraining the controller performance achieved. The book presents new techniques for the understanding of the iterative improvement of performance through the successive fitting of models using closed-loop data and the design of high-performance controllers using these models. The subject matter includes: New approaches to understanding how to affect the fit of dynamical models to physical processes through the choice of experiments, data pre-filtering and model structure; connections between robust control design methods and their dependency on the quality of model fit; experimental design in which data collected in operation under feedback can reveal areas that limit the performance achieved; iterative approaches to link these model-fitting and control design phases in a cogent manner so as to achieve improved performance overall. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.