The Foundations of Fuzzy Control

The Foundations of Fuzzy Control

The Foundations of Fuzzy Control

Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.

Foundations of Fuzzy Control

Foundations of Fuzzy Control

Foundations of Fuzzy Control

Foundations of Fuzzy Control: A Practical Approach, 2ndEdition has been significantly revised and updated, with twonew chapters on Gain Scheduling Control and Neurofuzzy Modelling.It focuses on the PID (Proportional, Integral, Derivative) typecontroller which is the most widely used in industry andsystematically analyses several fuzzy PID control systems andadaptive control mechanisms. This new edition covers the basics of fuzzy control and builds asolid foundation for the design of fuzzy controllers, by creatinglinks to established linear and nonlinear control theory. Advancedtopics are also introduced and in particular, common sense geometryis emphasised. Key features Sets out practical worked through problems, examples and casestudies to illustrate each type of control system Accompanied by a website hosting downloadable MATLABprograms Accompanied by an online course on Fuzzy Control which istaught by the author. Students can access further materialand enrol at the companion website Foundations of Fuzzy Control: A Practical Approach, 2ndEdition is an invaluable resource for researchers,practitioners, and students in engineering. It is especiallyrelevant for engineers working with automatic control ofmechanical, electrical, or chemical systems.

Foundations of Fuzzy Control

Foundations of Fuzzy Control

Foundations of Fuzzy Control

Fuzzy logic is key to the efficient working of many consumer, industrial and financial applications. Providing a brief history of the subject as well as analysing the system architecture of a fuzzy controller, this book gives a full and clearly set out introduction to the topic. As an essential guide to this subject for many engineering disciplines, Foundations of Fuzzy Control successfully exploits established results in linear and non-linear control theory. It presents a full coverage of fuzzy control, from basic mathematics to feedback control, all in a tutorial style. In particular this book: Systematically analyses several fuzzy PID (Proportional-Integral-Derivative) control systems and state space control, and also self-learning control mechanisms Sets out practical worked through problems, examples and case studies to illustrate each type of control system Provides an accompanying Web site that contains downloadable Matlab programs. This book is an invaluable resource for a broad spectrum of researchers, practitioners, and students in engineering. In particular it is especially relevant for those in mechanical and electrical engineering, as well as those in artificial intelligence, machine learning, bio-informatics, and operational research. It is also a useful reference for practising engineers, working on the development of fuzzy control applications and system architectures.

The Foundations of Fuzzy Control

The Foundations of Fuzzy Control

The Foundations of Fuzzy Control

Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.

Fuzzy Control and Modeling

Fuzzy Control and Modeling

Fuzzy Control and Modeling

The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design. Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth and rigorous. Numeric examples and applications illustrate the utility of the theoretical development. Important topics discussed include: Structures of fuzzy controllers/models with respect to conventional fuzzy controllers/models Analysis of fuzzy control and modeling in relation to their classical counterparts Stability analysis of fuzzy systems and design of fuzzy control systems Sufficient and necessary conditions on fuzzy systems as universal approximators Real-time fuzzy control systems for treatment of life-critical problems in biomedicine Fuzzy Control and Modeling is a self-contained, invaluable resource for professionals and students in diverse technical fields who aspire to analytically study fuzzy control and modeling.

Foundations of Generic Optimization

Foundations of Generic Optimization

Foundations of Generic Optimization

This is a comprehensive overview of the basics of fuzzy control, which also brings together some recent research results in soft computing, in particular fuzzy logic using genetic algorithms and neural networks. This book offers researchers not only a solid background but also a snapshot of the current state of the art in this field.

Fuzzy Logic Foundations and Industrial Applications

Fuzzy Logic Foundations and Industrial Applications

Fuzzy Logic Foundations and Industrial Applications

Fuzzy Logic Foundations and Industrial Applications is an organized edited collection of contributed chapters covering basic fuzzy logic theory, fuzzy linear programming, and applications. Special emphasis has been given to coverage of recent research results, and to industrial applications of fuzzy logic. The chapters are new works that have been written exclusively for this book by many of the leading and prominent researchers (such as Ronald Yager, Ellen Hisdal, Etienne Kerre, and others) in this field. The contributions are original and each chapter is self-contained. The authors have been careful to indicate direct links between fuzzy set theory and its industrial applications. Fuzzy Logic Foundations and Industrial Applications is an invaluable work that provides researchers and industrial engineers with up-to-date coverage of new results on fuzzy logic and relates these results to their industrial use.

Foundations of Fuzzy Logic and Soft Computing

Foundations of Fuzzy Logic and Soft Computing

Foundations of Fuzzy Logic and Soft Computing

Annotation This book comprises a selection of papers from IFSA 2007 on new methods and theories that contribute to the foundations of fuzzy logic and soft computing. These papers were selected from over 400 submissions and constitute an important contribution to the theory and applications of fuzzy logic and soft computing methodologies. Soft Computing consists of several computing paradigms, including fuzzy logic, neural networks, genetic algorithms, and other techniques, which can be used to produce powerful intelligent systems for solving real-world problems. This book is intended to be a major reference for scientists and engineers interested in applying new computational and mathematical tools to achieve intelligent solution to complex problems. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the papers contained in the book. The 80 papers presented were carefully reviewed and selected form more than 400 submissions. The papers are organized in topical sections on relation between interval and fuzzy techniques, intuitionistic fuzzy sets and their applications, the application of fuzzy logic and soft computing in flexible querying, philosophical and human-scientific aspects of soft computing, search engine and information processing and retrieval, perception based data mining and decision making, joint model-based and data-based learning: the fuzzy logic approach, fuzzy possibilistic optimization, fuzzy trees, fuzzy logic theory, type-2 fuzzy logic, fuzzy logic applications, neural networks and control, as well as intelligent agents and knowledge ant colony.

Foundations of Fuzzy Systems

Foundations of Fuzzy Systems

Foundations of Fuzzy Systems

A rigorous explanation of fuzzy systems theory plus a detailed illustration of specific practical applications of the powerful engineering tool they represent. Contains a discussion of cutting-edge technology supplemented by the analysis of several successful applications in the areas of approximate reasoning, fuzzy control and fuzzy analysis. Includes scores of exercises, problems, worked examples, step-by-step solutions and comprehensive references.

Foundations of Fuzzy Logic and Semantic Web Languages

Foundations of Fuzzy Logic and Semantic Web Languages

Foundations of Fuzzy Logic and Semantic Web Languages

Managing vagueness/fuzziness is starting to play an important role in Semantic Web research, with a large number of research efforts underway. Foundations of Fuzzy Logic and Semantic Web Languages provides a rigorous and succinct account of the mathematical methods and tools used for representing and reasoning with fuzzy information within Semantic