Systems and control by stanislaw h zak pdf

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systems and control by stanislaw h zak pdf

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Stanislaw H.

Mathematical Theory of Networks and Systems

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System Kendali - Systems and control 1. Published by Oxford University Press, Inc. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Oxford University Press.

Includes bibliographical references and index. ISBN 1. Linear control systems. Z35 Its objective is to familiarize the reader with the basics of dynamical system theory while, at the same time, equipping him or her with the tools necessary for control system design. Various methods of a controller design are discussed.

This text can be used in a variety of ways. It is suitable for a senior- or graduate-level course on systems and control. The text can also be used in an introductory course on nonlinear systems. Finally, it can be used in an introductory course to modern automatic control. No special background is necessary to read this text beyond basic differential equations and elements of linear algebra. The book is also suitable for self-study. To accomplish this goal, the required mathematical techniques and terminology are reviewed in the Appendix.

Depending on the background, the reader may refer to the material in the Appendix as needed. In this book we discuss mathematical modeling of problems from mechanical and electrical engineering, as well as from physics and biology. Constructing models of dynamical systems using a linguistic description that employs IF—THEN rules is also considered.

Two main types of dynamical systems are common in applications: those for which the time variable is discrete and those for which the time variable is continuous. When the time variable is discrete, the dynamics of such systems are often modeled using difference equations.

In the case when the time is continuous, ordinary differential equations are frequently chosen for modeling purposes. Both types of models are considered in the book. Nonlinear systems are emphasized to acknowledge the critical role that nonlinear phenomena play in science and technology. The models presented are the ones that can be used to design controllers. These models are constructed from the control engineering point of view. Most of the time, engineers develop models of man-made objects.

This is in contrast with physicists, who are more interested in modeling nature. Models in the last chapter of this book, however, are of interest to engineers, physicists, or biologists. This chapter is an invitation to control engineering of the future where control designers will be challenged to tackle highly complex, nonlinear, dynamical systems using multidisciplinary tools.

As can be concluded from the above remarks, the scope of the book is quite broad. This is in order to show the multidisciplinary role of nonlinear dynamics and control.

In particular, neural networks, fuzzy systems, and genetic algorithms are presented and a self-contained introduction to chaotic systems is provided. The objective of the stability analysis is to determine the xv 5. In fact, the Lyapunov theory is used as a unifying medium for different types of dynamical systems analyzed. In particular, optimal, fuzzy, sliding mode, and chaotic controllers are all constructed with the aid of the Lyapunov method and its variants.

It is shown how these new tools of a control engineer supplement the classical ones. In addition to worked examples, this book also contains exercises at the end of each chapter. A number of solved problems, as well as the exercises, require the use of a computer. The solutions manual, with complete solutions to all the exercises in the book, is available from the publisher to the instructors who adopt this book for their courses. Acknowledgments I am indebted to my wife, Mary Ann, and to my children, Michaela, George, Elliot, and Nick, for their support during the writing of this book.

I express my gratitude to numerous students on whom this text was tested. His insights and discussions helped clarify many concepts discussed in this book. Yonggon Lee contributed many simulations included in the book and in the solutions manual. It was a pleasant experience working with Peter Gordon, Justin Collins, and the staff of Oxford University Press during the production of the book.

Finally, I wish to thank the National Science Foundation for the much appreciated support during the last stages of this project. Errors found by the author or by readers are corrected every printing. Phone: , fax: , e-mail: info mathworks. Your prey, drawn to dark places, will probably head straight for the umbrella. Then quickly close it, go outside, and set your prisoner free.

A system is a collection of interacting components. An electric motor, an airplane, and a biological unit such as the human arm are examples of systems. A system is characterized by two properties, which are as follows: 1. The interrelations between the components that are contained within the system 2. The system boundaries that separate the components within the system from the components outside The system boundaries can be real or imagined.

They are elastic in the sense that we may choose, at any stage of the system analysis, to consider only a part of the original system as a system on its own. We call it a subsystem of the original system.

On the other hand, we may decide to expand the boundaries of the original system to include new components. In Figure 1. The interactions between the system components may be governed, for example, by physical, biological, or economical laws. In dealing with systems, we are interested in the effects of external quantities upon the behavior of the system quantities.

We refer to the external quantities acting on the system as the inputs to the system. The condition or the state of the system is described by the state variables. The state variables provide the information that, together with the knowledge of the system inputs, enables us to determine the future state of the system. An axiomatic description of a dynamical system is presented in Section 1. In practice it is often not possible or too expensive to measure or determine the values of all of the state variables.

Instead, only their subset or combination can be measured. The system quantities whose behavior can be measured or observed are referred to as the system outputs. That is, we are interested in controlling the system states or outputs.

An interconnection of the system and a controller is called a control system. In Figures 1. Constructing a controller is a part of the control problem.

ISBN 13: 9780195150117

Buy Ebook from VitalSource. This book discusses modeling, analysis, and control of dynamical systems. Systems and Control presents modeling, analysis, and control of dynamical systems. Introducing students to the basics of dynamical system theory and supplying them with the tools necessary for control system design, it emphasizes design and demonstrates how dynamical system theory fits into practical applications. Classical methods and the techniques of postmodern control engineering are presented in a unified fashion, demonstrating how the current tools of a control engineer can supplement more classical tools.

Systems and Control presents modeling, analysis, and control of dynamical systems. Introducing students to the basics of dynamical system theory and supplying them with the tools necessary for control system design, it emphasizes design and demonstrates how dynamical system theory fits into practical applications. Classical methods and the techniques of postmodern control engineering are presented in a unified fashion, demonstrating how the current tools of a control engineer can supplement more classical tools. Broad in scope, Systems and Control shows the multidisciplinary role of dynamics and control; presents neural networks, fuzzy systems, and genetic algorithms; and provides a self-contained introduction to chaotic systems. The text employs Lyapunov's stability theory as a unifying medium for different types of dynamical systems, using it--with its variants--to analyze dynamical system models. Specifically, optimal, fuzzy, sliding mode, and chaotic controllers are all constructed with the aid of the Lyapunov method and its extensions.


Systems and Control. Stanislaw H. Zak School of Electrical and Computer Engineering Purdue University. New York Oxford. OXFORD.


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Embed Size px x x x x Copyright c by Oxford University Press, Inc. Published by Oxford University Press, Inc. All rights reserved. No part of this publication may be reproduced,stored in a retrieval system, or transmitted, in any form or by any means,electronic, mechanical, photocopying, recording, or otherwise,without the prior permission of Oxford University Press. Includes bibliographical references and index.

COMMENT 3

  • Skip to main content Skip to table of contents. Finlay H. - 03.06.2021 at 17:33
  • A modern, up-to-date introduction to optimization theory and methods This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. Pansy C. - 05.06.2021 at 20:10
  • Systems and Control. Stanislaw H.˙Zak. School of Electrical and Computer Engineering. Purdue University. New York. Oxford. OXFORD UNIVERSITY PRESS. Marc M. - 08.06.2021 at 21:33

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