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Fuzzy Algorithms for Control gives an overview of the research results of a number of European research groups that are active and play a leading role in the field of fuzzy modeling and control. It contains 12 chapters divided into three parts.
Chapters in the first part address the position of fuzzy systems in control engineering and in the AI community. State-of-the-art surveys on fuzzy modeling and control are presented along with a critical assessment of the role of these methodologists in control engineering.
The second part is concerned with several analysis and design issues in fuzzy control systems. The analytical issues addressed include the algebraic representation of fuzzy models of different types, their approximation properties, and stability analysis of fuzzy control systems. Several design aspects are addressed, including performance specification for control systems in a fuzzy decision-making framework and complexity reduction in multivariable fuzzy systems.
In the third part of the book, a number of applications of fuzzy control are presented. It is shown that fuzzy control in combination with other techniques such as fuzzy data analysis is an effective approach to the control of modern processes which present many challenges for the design of control systems. One has to cope with problems such as process nonlinearity, time-varying characteristics for incomplete process knowledge. Examples of real-world industrial applications presented in this book are a blast furnace, a lime kiln and a solar plant. Other examples of challenging problems in which fuzzy logic plays an important role and which are included in this book are mobile robotics and aircraft control.
The aim of this book is to address both theoretical and practical subjects in a balanced way. It will therefore be useful for readers from the academic world and also from industry who want to apply fuzzy control in practice.
List of contents
I The Position and State of The Art of Fuzzy Systems.- 1 Fuzzy Systems in Control Engineering.- 2 Fuzzy Logic, Control Engineering and Artificial Intelligence.- 3 Fuzzy Control Versus Conventional Control.- 4 Data-Driven Construction of Transparent Fuzzy Models.- II Design and Analysis Issues.- 5 Fuzzy Logic Normal Forms for Control Law Representation.- 6 Stability Analysis of Fuzzy Control Loops.- 7 Performance Criteria: Classical and Fuzzy Design.- 8 Complexity Reduction Methods for Fuzzy Systems.- III Application of Fuzzy Systems.- 9 Intelligent Data Analysis and Fuzzy Control.- 10 Fuzzy Control in Process Industry.- 11 Fuzzy Logic Applications in Mobile Robotics.- 12 Enhancing Flight Control using Fuzzy Logic.
About the author
Prof. em. Dr. Drs. h. c. Hans-Jürgen Zimmermann war bis 1999 Inhaber des Lehrstuhls für Unternehmensforschung (Operations Research) an der RWTH Aachen und ist Wissenschaftlicher Leiter der ELITE (European Laboratory for Intelligent Techniques Engineering) sowie wissenschaftlicher Beirat des Instituts für Operations Research und Management, Inform GmbH, in Aachen.
Summary
It is shown that fuzzy control in combination with other techniques such as fuzzy data analysis is an effective approach to the control of modern processes which present many challenges for the design of control systems.
