Bücher der Reihe Advanced Textbooks in Control and Signal Processing

The only book on the subject at this level, this is a well written formalised and concise presentation of the basis of statistical signal processing. It teaches a wide variety of techniques, demonstrating how they can be applied to many different situations.

A typical method of dealing with input and output constraints, especially for PID control, has been the empirical design and implementation of an intuitive solution to an individual plant and its constraints. Such ad hoc solutions perform surprisingly well but often remain in the form of isolated practical know-how without a more general scientific basis.Control Systems with Input and Output Constraints develops this empirical approach by demonstrating how particular answers to particular industrial design problems can be systematized to cope with a wide variety of simple and more complex situations. Each class of design problems is presented in five parts: industrial situation; problem statement; currently available control structures; benchmark simulation to obtain typical transient response and nonlinear stability analysis to relate structure to response. Links to optimal control and model predictive control are also explored. These steps help the reader to learn how to choose or adapt a control architecture and design or analyse it on a systematic basis. Features:associated website contains many ready-made examples and case studies using Matlab®/Simulink® to which extensive reference is made throughout the text facilitating understanding and saving time;exercises interspersed throughout each chapter that allow the student to confirm progress as he/she proceeds;logical five-step design procedure for each problem class moving from a particular industrial example to the informed choice of generic controller and the preparation of closed loop analysis. Control Systems with Input and Output Constraints will be of great benefit to advanced students of control looking to pursue a career in process and/or plant control or in applications-oriented research. The practical basis of the presentation, the systematic design procedure, therestraint on mathematical formalism and emphasis on implementability will also appeal to industrial control engineers.

Modern power electronic converters are involved in a very broad spectrum of applications: switched-mode power supplies, electrical-machine-motion-control, active power filters, distributed power generation, flexible AC transmission systems, renewable energy conversion systems and vehicular technology, among them.Power Electronics Converters Modeling and Control teaches the reader how to analyze and model the behavior of converters and so to improve their design and control. Dealing with a set of confirmed algorithms specifically developed for use with power converters, this text is in two parts: models and control methods. The first is a detailed exposition of the most usual power converter models:* switched and averaged models;* small/large-signal models; and* time/frequency models.The second focuses on three groups of control methods:* linear control approaches normally associated with power converters;* resonant controllers because of their significance in grid-connected applications; and* nonlinear control methods including feedback linearization, stabilizing, passivity-based, and variable-structure control.Extensive case-study illustration and end-of-chapter exercises reinforce the study material.Power Electronics Converters Modeling and Control addresses the needs of graduate students interested in power electronics, providing a balanced understanding of theoretical ideas coupled with pragmatic tools based on control engineering practice in the field. Academics teaching power electronics will find this an attractive course text and the practical points make the book useful for self tuition by engineers and other practitioners wishing to bring their knowledge up to date.

The topics of control engineering and signal processing continue to flourish and develop. In common with general scientific investigation, new ideas, concepts and interpretations emerge quite spontaneously and these are then discussed, used, discarded or subsumed into the prevailing subject paradigm. Sometimes these innovative concepts coalesce into a new sub-discipline within the broad subject tapestry ofcontrol and signal processing. This preliminary batde between old and new usually takes place at conferences, through the Internet and in the journals of the discipline. After a litde more maturity has been acquiredhas been acquired by the new concepts then archival publication as ascientificorengineering monograph mayoccur. Anewconceptin control and signal processing is known to have arrived when sufficient material has developed for the topic to be taught as a specialised tutorial workshop or as a course to undergraduates, graduates or industrial engineers. The Advanced Textbooks in Control and Signal Processing Series is designed as a vehicle for the systematic presentation ofcourse material for both popular and innovative topics in the discipline. It is hoped that prospective authors will welcome the opportunity to publish a structured presentation of either existing subject areas or some of the newer emerging control and signal processing technologies.

MATLAB (R) files supplied to assist in working through exercises and examples. Solutions manual pdf.

In order to deepen readers' understanding, simpler single-input-single-output systems generally precede treatment of more complex multi-input-multi-output (MIMO) systems and linear systems precede nonlinear systems.

MATLAB (R) files supplied to assist in working through exercises and examples. Solutions manual pdf.

Dead-time-process-control problems are studied using classical proportional-integral-differential (PID) control for the simpler examples and dead-time-compensator (DTC) and model predictive control (MPC) methods for progressively more complex ones.

Following an introduction on system theory, this book shows the reader how to approach the system identification problem in a systematic fashion. It aims to teach students the fundamentals of systems identification without unduly complicated mathematics.

This comprehensive and up-to-date book focuses on an algebraic approach to the analysis and design of discrete-time signal processors, including material applicable to numeric and symbolic computation programs such as MATLAB. Written with clarity, it contains the latest detailed research results.

A comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing how it can be used for system identification and control.

Robotics provides the know-how on the foundations of robotics: modelling, planning and control. It covers mobile robots, visual control and motion planning. A variety of problems are worked through, and the tools to find engineering solutions are explained.

This book introduces the advantages of parallel processing and details how to use it to deal with common signal processing and control algorithms. The text includes examples and end-of-chapter exercises, and case studies to put theoretical concepts into a practical context.

The book presents a clear understanding of a new type of computation system, the Cellular Neural Network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations.

Introduces the proper tools to find engineering-oriented solutions. This book includes fundamental coverage of kinematics, statics and dynamics of manipulators, and trajectory planning and motion control in free space. It offers technological aspects that include hardware- and software-control architectures and industrial robot-control algorithms.

Robust Control Design with MATLAB (R) (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases.

This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.

Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs.

This comprehensive book gives a overview of the latest discussions in the application of genetic algorithms to solve engineering problems. Featuring real-world applications and an accompanying disk, giving the reader the opportunity to use an interactive genetic algorithms demonstration program.

This MATLAB exercise book accompanies the textbook Control Engineering, providing a platform for students to practice problem solving in the analysis and design of continuous and discrete control problems reflected in the main textbook.

The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners.