Synopses & Reviews
A self-contained introduction to algebraic control for nonlinear systems suitable for researchers and graduate students. The most popular treatment of control for nonlinear systems is from the viewpoint of differential geometry yet this approach proves not to be the most natural when considering problems like dynamic feedback and realization. Professors Conte, Moog and Perdon develop an alternative linear-algebraic strategy based on the use of vector spaces over suitable fields of nonlinear functions. This algebraic perspective is complementary to, and parallel in concept with, its more celebrated differential-geometric counterpart. Algebraic Methods for Nonlinear Control Systems describes a wide range of results, some of which can be derived using differential geometry but many of which cannot. They include: • classical and generalized realization in the nonlinear context; • accessibility and observability recast within the linear-algebraic setting; • discussion and solution of basic feedback problems like input-to-output linearization, input-to-state linearization, non-interacting control and disturbance decoupling; • results for dynamic and static state and output feedback. Dynamic feedback and realization are shown to be dealt with and solved much more easily within the algebraic framework. Originally published as Nonlinear Control Systems, 1-85233-151-8, this second edition has been completely revised with new text - chapters on modeling and systems structure are expanded and that on output feedback added de novo - examples and exercises. The book is divided into two parts: the first being devoted to the necessary methodology and the second to an exposition of applications to control problems.
Review
From the reviews of the second edition: "Algebraic Methods for Nonlinear Control Systems is a book published under the Springer Communication and Control Engineering publication program, which presents major technological advances within these fields. The book aims at presenting one of the two approaches to nonlinear control systems, namely the differential algebraic method. ... is an excellent textbook for graduate courses on nonlinear control systems. ... The differential algebraic method presented in this book appears to be an excellent tool for solving the problems associated with nonlinear systems." (Dariusz Bismor, International Journal of Acoustics and Vibration, Vol. 14 (4), 2009)
Synopsis
This is a self-contained introduction to algebraic control for nonlinear systems suitable for researchers and graduate students. It is the first book dealing with the linear-algebraic approach to nonlinear control systems in such a detailed and extensive fashion. It provides a complementary approach to the more traditional differential geometry and deals more easily with several important characteristics of nonlinear systems.
Synopsis
This volume provides a detailed introduction to algebraic control for nonlinear systems. It is divided into two parts: necessary methodology and applications to control problems. The book develops an alternative linear-algebraic strategy based on the use of vector spaces over suitable fields of nonlinear functions. This algebraic perspective is complementary to, and parallel in concept with, its more celebrated differential-geometric counterpart and deals more easily with several important characteristics of nonlinear systems. It describes a wide range of results, some of which can be derived using differential geometry but many of which cannot. They include: classical and generalized realization in the nonlinear context; accessibility and observability recast within the linear-algebraic setting; and results for dynamic and static state and output feedback. This second edition has been completely revised with new text, examples and exercises.
Table of Contents
Part I: Methodology.- Preliminaries.- Modeling.- Accessibility.- Observability.- Systems Structure and Inversion.- System Transformations.- Part II: Applications to Control Problems.- Input-Output Linearization.- Noninteracting Control.- Input-State Linearization.- Disturbance Decoupling.- Model Matching.- Measured Output Feedback Control Problems.