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Control and Dynamic Systems: Advances in Theory and Application, Volume 51: Robust Control System Techniques and Applications Part 2 of 2 discusses system robustness techniques. This volume presents a comprehensive treatment of robust system techniques in nonlinear, linear, and multilinear interval systems. It also covers techniques for dealing with system disturbances, system modeling approximations, and parameter uncertainties. This volume ends by reviewing robustness techniques for systems with structured state space uncertainty. This volume will be of great use as a reference source for mechanical and electrical engineers.
Control and Dynamic Systems: Advances in Theory and Applications, Volume 50: Robust Control System Techniques and Applications, Part 1 of 2 is a two-volume sequence devoted to the issues and application of robust control systems techniques. This volume is composed of 10 chapters and begins with a presentation of the important techniques for dealing with conflicting design objectives in control systems. The subsequent chapters describe the robustness techniques of systems using differential-difference equations; the design of a wide class of robust nonlinear systems, the techniques for dealing with the problems resulting from the use of observers in robust systems design, and the effective techniques for the robust control on non-linear time varying of tracking control systems with uncertainties. These topics are followed by discussions of the effective techniques for the robust control on non-linear time varying of tracking control systems with uncertainties and for incorporating adaptive control techniques into a (non-adaptive) robust control design. Other chapters present techniques for achieving exponential and robust stability for a rather general class of nonlinear systems, techniques in modeling uncertain dynamics for robust control systems design, and techniques for the optimal synthesis of these systems. The last chapters provide a generalized eigenproblem solution for both singular and nonsingular system cases. These chapters also look into the stability robustness design for discrete-time systems. This book will be of value to process and systems engineers, designers, and researchers.
"The purpose of this book is to present the theory of control and coordination in hierarchical systems - that is, in systems where the decision-making responsibility has been divided. Since it aims to present theory that will be useful for applications, it not only encompasses the basic, general, and consequently somewhat abstract principles of coordination, but also considers such practical features as differences between models and the reality they describe, constraints, possible use of feedback information, and time horizons." --Preface.
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This authoritative treatment covers theory, optimal estimation and a range of practical applications. The first book on the subject, and written by leading researchers, this clear and rigorous work presents a comprehensive theory for both the stability boundary and the stability regions of a range of nonlinear dynamical systems including continuous, discrete, complex, two-time-scale and non-hyperbolic systems, illustrated with numerical examples. The authors also propose new concepts of quasi-stability region and of relevant stability regions and their complete characterisations. Optimal schemes for estimating stability regions of general nonlinear dynamical systems are also covered, and finally the authors describe and explain how the theory is applied in applications including direct methods for power system transient stability analysis, nonlinear optimisation for finding a set of high-quality optimal solutions, stabilisation of nonlinear systems, ecosystem dynamics, and immunisation problems.
Well-written, practice-oriented textbook, and compact textbook Presents the contemporary state of the art of control theory and its applications Introduces traditional problems that are useful in the automatic control of technical processes, plus presents current issues of control Explains methods can be easily applied for the determination of the decision algorithms in computer control and management systems