Ebook: Fuzzy Algorithms for Control

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.

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Content:
Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Fuzzy Systems in Control Engineering....Pages 3-15
Fuzzy Logic, Control Engineering and Artificial Intelligence....Pages 17-57
Fuzzy Control Versus Conventional Control....Pages 59-81
Data-Driven Construction of Transparent Fuzzy Models....Pages 83-106
Front Matter....Pages 109-109
Fuzzy Logic Normal Forms for Control Law Representation....Pages 111-125
Stability Analysis of Fuzzy Control Loops....Pages 127-157
Performance Criteria: Classical and Fuzzy Design....Pages 159-183
Complexity Reduction Methods for Fuzzy Systems....Pages 185-218
Front Matter....Pages 221-221
Intelligent Data Analysis and Fuzzy Control....Pages 223-242
Fuzzy Control in Process Industry: The Linguistic Equation Approach....Pages 243-300
Fuzzy Logic Applications in Mobile Robotics....Pages 301-324
Enhancing Flight Control using Fuzzy Logic....Pages 325-348
Back Matter....Pages 349-352

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Content:
Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Fuzzy Systems in Control Engineering....Pages 3-15
Fuzzy Logic, Control Engineering and Artificial Intelligence....Pages 17-57
Fuzzy Control Versus Conventional Control....Pages 59-81
Data-Driven Construction of Transparent Fuzzy Models....Pages 83-106
Front Matter....Pages 109-109
Fuzzy Logic Normal Forms for Control Law Representation....Pages 111-125
Stability Analysis of Fuzzy Control Loops....Pages 127-157
Performance Criteria: Classical and Fuzzy Design....Pages 159-183
Complexity Reduction Methods for Fuzzy Systems....Pages 185-218
Front Matter....Pages 221-221
Intelligent Data Analysis and Fuzzy Control....Pages 223-242
Fuzzy Control in Process Industry: The Linguistic Equation Approach....Pages 243-300
Fuzzy Logic Applications in Mobile Robotics....Pages 301-324
Enhancing Flight Control using Fuzzy Logic....Pages 325-348
Back Matter....Pages 349-352
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