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Introduction to state-space methods covers feedback control; state-space representation of dynamic systems and dynamics of linear systems; frequency-domain analysis; controllability and observability; shaping the dynamic response; more. 1986 edition.
Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers’ assimilation of the material discussed is assisted by the provision of problems and examples. Most of these exercises use MATLAB® to make computation and visualization more straightforward. Applied Control System Design will be of interest to academic researchers for its comparison of different systems models and their response to different control methods and will assist graduate students in learning the practical necessities of advanced control system design. The consistent reference to real systems coupled with self-learning tools will assist control practitioners who wish to keep up to date with the latest control design ideas.
The extraordinary development of digital computers (microprocessors, microcontrollers) and their extensive use in control systems in all fields of applications has brought about important changes in the design of control systems. Their performance and their low cost make them suitable for use in control systems of various kinds which demand far better capabilities and performances than those provided by analog controllers. However, in order really to take advantage of the capabilities of microprocessors, it is not enough to reproduce the behavior of analog (PID) controllers. One needs to implement specific and high-performance model based control techniques developed for computer-controlled systems (techniques that have been extensively tested in practice). In this context identification of a plant dynamic model from data is a fundamental step in the design of the control system. The book takes into account the fact that the association of books with software and on-line material is radically changing the teaching methods of the control discipline. Despite its interactive character, computer-aided control design software requires the understanding of a number of concepts in order to be used efficiently. The use of software for illustrating the various concepts and algorithms helps understanding and rapidly gives a feeling of the various phenomena.
This book presents developments in analysis and design techniques for control systems. Included are exciting results for feedback systems using complex variable methods, the important concept of robustness in controller design and the increasingly important topic of decentralized control for large scale systems. These and many other contributions illustrate the great activity and rapid progress which has taken place in the subject over the past few years. Only by bringing these contributions together under one cover can the practising engineer in industry and indeed the engineer in university or polytechnic keep fully informed on the 'state of the art' on a number of different fronts. Application of the theoretical developments and practical aspects of the subject are not forgotten; analysis and design of a nuclear boiler and some direct digital control system design procedures are but two topics discussed in the present book. Several of the chapters are followed by problems on the subject matter and worked solutions to most of these problems are given at the end of the book. This aspect will find favour with many readers since such contributions are often a great help in the understanding of the subject matter.
Using a "how to do it" approach with a strong emphasis on real-world design, this book provides comprehensive,single-source coverage of the full spectrum of control system design. Each of the book's 8 parts covers a specific area of control--ranging from signals and systems (Bode Diagrams, Root Locus, etc.), to SISO control (including PID and Fundamental Design Trade-offs) and MIMO systems (including Constraints, MPC, Decoupling, etc.). Features an abundance of real-world design examples drawn from the authors' direct experience, and many real-world case studies divided intoIndustrial case studies and Laboratory systems (several of which are supported by a virtual laboratory using Java Applets on the book's web page). All examples are supported by Matlab®.The Excitement of Control Engineering. Introduction to the Principles of Feedback. Modeling. Continuous Time Signals and Systems. Analysis of SISO Control Loops. Classical PID Control. Synthesis of SISO Controllers. Fundamental Limitations in SISO Control. Frequency Domain Design Limitations. Architectural Issues in SISO Control. Dealing with Constraints. Models for Sampled Data Systems. Digital Control. Hybrid Control. SISO Controller Parameterizations. Control Design Based on Optimization. Linear State Space Models. Synthesis via State Space Methods. Introduction to Nonlinear Control. Analysis of MIMO Control Loops. Exploiting SISO Techniques in MIMO Control. Design via Optimal Control Techniques. Model Predictive Control. Fundamental Limitations in MIMO Control. MIMO Controller Parameterizations. Decoupling. For anyone interested in Control System Design.
A comprehensive treatment of model-based fuzzy control systems This volume offers full coverage of the systematic framework for the stability and design of nonlinear fuzzy control systems. Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wang address a number of important issues in fuzzy control systems, including stability analysis, systematic design procedures, incorporation of performance specifications, numerical implementations, and practical applications. Issues that have not been fully treated in existing texts, such as stability analysis, systematic design, and performance analysis, are crucial to the validity and applicability of fuzzy control methodology. Fuzzy Control Systems Design and Analysis addresses these issues in the framework of parallel distributed compensation, a controller structure devised in accordance with the fuzzy model. This balanced treatment features an overview of fuzzy control, modeling, and stability analysis, as well as a section on the use of linear matrix inequalities (LMI) as an approach to fuzzy design and control. It also covers advanced topics in model-based fuzzy control systems, including modeling and control of chaotic systems. Later sections offer practical examples in the form of detailed theoretical and experimental studies of fuzzy control in robotic systems and a discussion of future directions in the field. Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.
Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements. Providing a range of solutions to control and signal processing problems, this book: * Presents a comprehensive introduction to the polynomial systems approach for the solution of H_2 and H_infinity optimal control problems. * Develops robust control design procedures using frequency domain methods. * Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. * Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. * Considers time-varying control and signal processing problems. * Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.

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