The Industrial Electronics Handbook SEcond EdITIon IntellIgent systems © 2011 by Taylor and Francis Group, LLC The Industrial Electronics Handbook SEcond EdITIon Fundamentals oF IndustrIal electronIcs Power electronIcs and motor drIves control and mechatronIcs IndustrIal communIcatIon systems IntellIgent systems © 2011 by Taylor and Francis Group, LLC The Electrical Engineering Handbook Series Series Editor Richard C. Dorf University of California, Davis Titles Included in the Series The Avionics Handbook, Second Edition, Cary R. Spitzer The Biomedical Engineering Handbook, Third Edition, Joseph D. Bronzino The Circuits and Filters Handbook, Third Edition, Wai-Kai Chen The Communications Handbook, Second Edition, Jerry Gibson The Computer Engineering Handbook, Vojin G. Oklobdzija The Control Handbook, Second Edition, William S. Levine CRC Handbook of Engineering Tables, Richard C. Dorf Digital Avionics Handbook, Second Edition, Cary R. 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Bishop The Mobile Communications Handbook, Second Edition, Jerry D. Gibson The Ocean Engineering Handbook, Ferial El-Hawary The RF and Microwave Handbook, Second Edition, Mike Golio The Technology Management Handbook, Richard C. Dorf Transforms and Applications Handbook, Third Edition, Alexander D. Poularikas The VLSI Handbook, Second Edition, Wai-Kai Chen © 2011 by Taylor and Francis Group, LLC The Industrial Electronics Handbook SEcond EdITIon IntellIgent systems Edited by Bogdan M. david Irwin © 2011 by Taylor and Francis Group, LLC MATLAB® is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book. This book’s use or discussion of MATLAB® software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular pedagogical approach or particular use of the MATLAB® software. 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Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging‑in‑Publication Data Intelligent systems / editors, Bogdan M.” Includes bibliographical references and index. Intelligent control systems.3’2--dc22 2010020581 Visit the Taylor & Francis Web site at http://www.com and the CRC Press Web site at http://www.com © 2011 by Taylor and Francis Group, LLC Contents Preface. xiii Editorial Board. xvii Contributors����������������������������������尓������������������������������������尓������������������������������������尓� xxi Part Iâ•… Introductions 1 Introduction to Intelligent Systems. 1-1 Ryszard Tadeusiewicz 2 From Backpropagation to Neurocontrol. Werbos 3 Neural Network–Based Control. 3-1 Mehmet Önder Efe 4 Fuzzy Logic–Based Control Section. 4-1 Mo-Yuen Chow Part IIâ•… Neural Networks 5 Understanding Neural Networks. Wilamowski 6 Neural Network Architectures. Wilamowski 7 Radial-Basis-Function Networks. Eide, Thomas Lindblad, and Guy Paillet 8 GMDH Neural Networks. 8-1 Marcin Mrugalski and Józef Korbicz vii © 2011 by Taylor and Francis Group, LLC viii Contents 9 Optimization of Neural Network Architectures. 9-1 Andrzej Obuchowicz 10 Parity-N Problems as a Vehicle to Compare Efficiencies of Neural Network Architectures. Wilamowski, Hao Yu, and Kun Tao Chung 11 Neural Networks Learning. Wilamowski 12 Levenberg–Marquardt Training. 12-1 Hao Yu and Bogdan M. Wilamowski 13 NBN Algorithm. Wilamowski, Hao Yu, and Nicholas Cotton 14 Accelerating the Multilayer Perceptron Learning Algorithms. 14-1 Sabeur Abid, Farhat Fnaiech, and Barrie W. Jervis 15 Feedforward Neural Networks Pruning Algorithms. 15-1 Nader Fnaiech, Farhat Fnaiech, and Barrie W. Jervis 16 Principal Component Analysis. 16-1 Anastasios Tefas and Ioannis Pitas 17 Adaptive Critic Neural Network Control. 17-1 Gary Yen 18 Self-Organizing Maps. 18-1 Gary Yen Part IIIâ•… Fuzzy Systems 19 Fuzzy Logic Controllers. 19-1 Teresa Orlowska-Kowalska and Krzysztof Szabat 20 Neuro-Fuzzy System. 20-1 Tiantian Xie, Hao Yu, and Bogdan M. Wilamowski 21 Introduction to Type-2 Fuzzy Logic Controllers. 21-1 Hani Hagras 22 Fuzzy Pattern Recognition. 22-1 Witold Pedrycz 23 Fuzzy Modeling of Animal Behavior and Biomimcry: The Fuzzy Ant. 23-1 Valeri Rozin and Michael Margaliot Part IVâ•… Optimizations 24 Multiobjective Optimization Methods.24-1 Tak Ming Chan, Kit Sang Tang, Sam Kwong, and Kim Fung Man © 2011 by Taylor and Francis Group, LLC Contents ix 25 Fundamentals of Evolutionary Multiobjective Optimization. Coello Coello 26 Ant Colony Optimization. 26-1 Christian Blum and Manuel López-Ibáñez 27 Heuristics for Two-Dimensional Bin-Packing Problems. 27-1 Tak Ming Chan, Filipe Alvelos, Elsa Silva, and J. Valério de Carvalho 28 Particle Swarm Optimization. 28-1 Adam Slowik Part Vâ•…Applications 29 Evolutionary Computation. 29-1 Adam Slowik 30 Data Mining. 30-1 Milos Manic 31 Autonomous Mental Development. 31-1 Juyang Weng 32 Synthetic Biometrics for Testing Biometric Systems and User Training. Yanushkevich, Adrian Stoica, Ronald R. Yager, Oleg Boulanov, and Vlad P. Index-1 © 2011 by Taylor and Francis Group, LLC Preface The field of industrial electronics covers a plethora of problems that must be solved in industrial prac- tice. Electronic systems control many processes that begin with the control of relatively simple devices like electric motors, through more complicated devices such as robots, to the control of entire fabrica- tion processes. An industrial electronics engineer deals with many physical phenomena as well as the sensors that are used to measure them. Thus, the knowledge required by this type of engineer is not only traditional electronics but also specialized electronics, for example, that required for high-power appli- cations. The importance of electronic circuits extends well beyond their use as a final product in that they are also important building blocks in large systems, and thus the industrial electronics engineer must also possess knowledge of the areas of control and mechatronics. Since most fabrication processes are relatively complex, there is an inherent requirement for the use of communication systems that not only link the various elements of the industrial process but are also tailor-made for the specific indus- trial environment. Finally, the efficient control and supervision of factories require the application of intelligent systems in a hierarchical structure to address the needs of all components employed in the production process. This need is accomplished through the use of intelligent systems such as neural networks, fuzzy systems, and evolutionary methods. The Industrial Electronics Handbook addresses all these issues and does so in five books outlined as follows: 1. Fundamentals of Industrial Electronics 2. Power Electronics and Motor Drives 3. Control and Mechatronics 4. Industrial Communication Systems 5. Intelligent Systems The editors have gone to great lengths to ensure that this handbook is as current and up to date as pos- sible. Thus, this book closely follows the current research and trends in applications that can be found in IEEE Transactions on Industrial Electronics. This journal is not only one of the largest engineering publications of its type in the world, but also one of the most respected. In all technical categories in which this journal is evaluated, it is ranked either number 1 or number 2 in the world. As a result, we believe that this handbook, which is written by the world’s leading researchers in the field, presents the global trends in the ubiquitous area commonly known as industrial electronics. An interesting phenomenon that has accompanied the progression of our civilization is the system- atic replacement of humans by machines. As far back as 200 years ago, human labor was replaced first by steam machines and later by electrical machines. Then approximately 20 years ago, clerical and sec- retarial jobs were largely replaced by personal computers. Technology has now reached the point where intelligent systems are replacing human intelligence in decision-making processes as well as aiding in the solution of very complex problems. In many cases, intelligent systems are already outperforming human activities. The field of computational intelligence has taken several directions. Artificial neural networks are not only capable of learning how to classify patterns, for example, images or sequences of xi © 2011 by Taylor and Francis Group, LLC xii Preface events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system behavior—as an example, measuring the system parameters that are easily obtainable and using a neural network to evaluate parameters that are difficult to measure but essential for system control. Fuzzy systems have a similar application. Their main advantage is their simplicity and ease of implementation. Various aspects of neural networks and fuzzy systems are covered in Parts II and III. Part IV is devoted to system optimization, where several new techniques including evolutionary meth- ods, swarm, and ant colony optimizations are covered. Part V is devoted to several applications that deal with methods of computational intelligence. For MATLAB • and Simulink• product information, please contact The MathWorks, Inc. 3 Apple Hill Drive Natick, MA, 01760-2098 USA Tel: 508-647-7000 Fax: 508-647-7001 E-mail: info@mathworks.com Web: www.com © 2011 by Taylor and Francis Group, LLC Acknowledgments The editors wish to express their heartfelt thanks to their wives Barbara Wilamowski and Edie Irwin for their help and support during the execution of this project. xiii © 2011 by Taylor and Francis Group, LLC Editorial Board Mo-Yuen Chow Witold Pedrycz North Carolina State University University of Alberta Raleigh, North Carolina Edmonton, Alberta, Canada Jósef Korbicz Ryszard Tadeusiewicz University of Zielona Góra AGH University of Science and Technology Zielona Góra, Poland Krakow, Poland Kim Fung Man Paul J. Werbos City University of Hong Kong National Science Foundation Kowloon, Hong Kong Arlington, Virginia Milos Manic Gary Yen University of Idaho, Idaho Falls Oklahoma State University Idaho Falls, Idaho Stillwater, Oklahoma xv © 2011 by Taylor and Francis Group, LLC Editors Bogdan M. Wilamowski received his MS in computer engineering in 1966, his PhD in neural computing in 1970, and Dr. in integrated circuit design in 1977. He received the title of full professor from the president of Poland in 1987.
