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A graduate text providing broad coverage of linear multivariable control systems, including several new results and recent approaches.
Multivariable Control Systems focuses on control design with continual references to the practical aspects of implementation. While the concepts of multivariable control are justified, the book emphasises the need to maintain student interest and motivation over exhaustive mathematical proof. Tools of analysis and representation are always developed as methods for achieving a final control system design and evaluation. Features: • design implementation laid out using extensive reference to MATLAB®; • combined consideration of systems (plant) and signals (mainly disturbances); • step-by-step approach from the objectives of multivariable control to the solution of complete design problems. Multivariable Control Systems is an ideal text for graduate students or for final-year undergraduates looking for more depth than provided by introductory textbooks. It will also interest the control engineer practising in industry and seeking to implement robust or multivariable control solutions to plant problems.
In wntmg this monograph my aim has been to present a "geometric" approach to the structural synthesis of multivariable control systems that are linear, time-invariant and of finite dynamic order. The book is ad dressed to graduate students specializing in control, to engineering scientists involved in control systems research and development, and to mathemati cians interested in systems control theory. The label "geometric" in the title is applied for several reasons. First and obviously, the setting is linear state space and the mathematics chiefly linear algebra in abstract (geometric) style. The basic ideas are the familiar system concepts of controllability and observability, thought of as geometric prop erties of distinguished state subspaces. Indeed, the geometry was first brought in out of revulsion against the orgy of matrix manipulation which linear control theory mainly consisted of, around fifteen years ago. But secondly and of greater interest, the geometric setting rather quickly sug gested new methods of attacking synthesis which have proved to be intuitive and economical; they are also easily reduced to matrix arithmetic as soon as you want to compute. The essence of the "geometric" approach is just this: instead of looking directly for a feedback law (say u = Fx) which would solve your synthesis problem if a solution exists, first characterize solvability as a verifiable property of some constructible state subspace, say Y. Then, if all is well, you may calculate F from Y quite easily.
Multivariable Feedback Control: Analysis and Design, Second Edition presents a rigorous, yet easily readable, introduction to the analysis and design of robust multivariable control systems. Focusing on practical feedback control and not on system theory in general, this book provides the reader with insights into the opportunities and limitations of feedback control. Taking into account the latest developments in the field, this fully revised and updated second edition: * features a new chapter devoted to the use of linear matrix inequalities (LMIs); * presents current results on fundamental performance limitations introduced by RHP-poles and RHP-zeros; * introduces updated material on the selection of controlled variables and self-optimizing control; * provides simple IMC tuning rules for PID control; * covers additional material including unstable plants, the feedback amplifier, the lower gain margin and a clear strategy for incorporating integral action into LQG control; * includes numerous worked examples, exercises and case studies, which make frequent use of Matlab and the new Robust Control toolbox. Multivariable Feedback Control: Analysis and Design, Second Edition is an excellent resource for advanced undergraduate and graduate courses studying multivariable control. It is also an invaluable tool for engineers who want to understand multivariable control, its limitations, and how it can be applied in practice. The analysis techniques and the material on control structure design should prove very useful in the new emerging area of systems biology. Reviews of the first edition: "Being rich in insights and practical tips on controller design, the book should also prove to be very beneficial to industrial control engineers, both as a reference book and as an educational tool." Applied Mechanics Reviews "In summary, this book can be strongly recommended not only as a basic text in multivariable control techniques for graduate and undergraduate students, but also as a valuable source of information for control engineers." International Journal of Adaptive Control and Signal Processing
This textbook is designed for an advanced course in control theory. The purpose of Chapter 1 is to introduce some results on the stability of dynamic systems achieved with the Lyapunov theory, and on its use for the synthesis of nonlinear control laws. The definition of norms and gains of dynamic systems is reported in Chapter 2 to provide the reader with the mathematical tools required in the following chapters. Some basic techniques for the analysis and the control of single-input, single-output systems are recalled in Chapter 3 to motivate the introduction, in the following chapters, of synthesis techniques for multi-input, multi-output systems. The analysis of multivariable systems, in terms of poles and zeros, manipulation rules of block diagrams, frequency response, stability of the feedback system, and static and dynamic performance, are discussed in Chapters 4 and 5. In Chapter 6 the pole-placement approach for the synthesis of state feedback control laws and state observers is described. Optimal control synthesis techniques for continuous- time systems are presented from Chapter 7 to 10. Specifically, the Linear Quadratic control method, the Kalman filter and the LQG control are widely described together with their main properties. These results are then extended to the discrete-time case in Chapter 11. The main algorithms and results of Model Predictive Control are finally presented in Chapter 12. Some useful mathematical notions are summarized in the Appendix. • stability • Lyapunov theory • multivariable systems • pole placement • state observers • optimal control • linear quadratic control • Kalman filter • LQG control • model predictive control
This reference/text discusses the structure and concepts of multivariable control systems, offering a balanced presentation of theory, algorithm development, and methods of implementation.;The book contains a powerful software package - L.A.S (Linear Algebra and Systems) which provides a tool for verifying an analysis technique or control design.;Reviewing the fundamentals of linear algebra and system theory, Algorithms for Computer-Aided Design of Multivariable Control Systems: supplies a solid basis for understanding multivariable systems and their characteristics; highlights the most relevant mathematical developments while keeping proofs and detailed derivations to a minimum; emphasizes the use of computer algorithms; provides special sections of application problems and their solutions to enhance learning; presents a unified theory of linear multi-input, multi-output (MIMO) system models; and introduces new results based on pseudo-controllability and pseudo-observability indices, furnishing algorithms for more accurate internodel conversions.;Illustrated with figures, tables and display equations and containing many previously unpublished results, Algorithms for Computer-Aided Design of Multivariable Control Systems is a reference for electrical and electronics, mechanical and control engineers and systems analysts as well as a text for upper-level undergraduate, graduate and continuing-education courses in multivariable control.