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.
