Microelectronic Design of Fuzzy Logic-Based Systems PDF
Preview Microelectronic Design of Fuzzy Logic-Based Systems
Plants of Central Asia Volume 8c M KROELECIROM C DESIGN OF HIZZY LOGIC-BASED SYSTEMS The CRC Press International Series on Computational Intelligence Series Editor l.C. lain, PhD., M.E., B.E. (Hons), Fellow I.E. (Australia) L.C. Jain, R.P. Johnson, Y. Takefuji, and LA. Zadeh Knowledge-Based Intelligent Techniques in Industry L.C. Jain and C.W. de Silva intelligent Adaptive Control: Industrial Applications in the Applied Computational Intelligence Set L.C. Jain and N.M. Martin Fusion of Neural Networks, Fuzzy Systems, and Genetic Algorithms: Industrial Applications H.-N. Teodorescn, A. Kandel, and L.C. Jain Fuzzy and Neuro-Fuzzy Systems in Medicine C.L. Karr and L.M. Freeman Industrial Applications of Genetic Algorithms L.C. Jain and B. Lazzerini Knowledge-Based Intelligent Techniques in Character Becognition L.C. Jain and K Vemuri industrial Applications of Neural Networks H.-N. Teodorescu, A. Kandel, and L.C. Jain Soft Computing in Human-Belated Sciences B. Lazzerini, D. Dumitrescu, L.C. Jain, and A. Dumitrescu Evolutionary Computing and Applications B. Lazzerini, D. Dumitrescu, and L.C. Jain Fuzzy Sets and Their Application to Clustering and Training L.C. Jain, U. Halici, I. Hayashi, S.B. Lee, and S. Tsutsui Intelligent Biometric Techniques in Fingerprint and Face Becognition Z. Chen Computational Intelligence for Decision Support L.C. Jain Evolution of Engineering and Information Systems and Their Applications H.-N. Teodorescu and A. Kandel Dynamic Fuzzy Systems and Chaos Applications L. Medsker and L.C. Jain Recurrent Neural Networks: Design and Applications L. C. Jain and A.M. Fanelli Recent Advances in Artifical Neural Networks: Design and Applications M. Russo and L.C. Jain Fuzzy Learning and Applications J. Liu Multiagent Hobotic Systems M. Kennedy, R. Rovatti, and G. Setti Chaotic Electronics in Telecommunications H. -N. Teodorescu and L.C. Jain intelligent Systems and Techniques in Rehabilitation Engineering I. Batnrone, A. Barriga, S. Sdnchez-Solano, C.J. Jimenez-Fernandez, and D.R. Lope Microelectronic Design of Fuzzy Logic-Dased Systems T. Nishida Dynamic Knowledge Interaction C.L. Karr Practical Applications of Computational Intelligence for Adaptive Control MICROELECTRONIC DESIGN OF FUZZY LOGIC-BASED SYSTEMS I. Baturone, A. Barriga, S. Sanchez-Solano, C.l. Jimenez-Fernandez, and B. B. Ltipez Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2000 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works ISBN 13: 978-0-8493-0091-2 (hbk) This book contains information obtained from authentic and highly regarded sources. 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Foreword During the last 35 years fuzzy logic has evolved from a mathematical cu riosity to a mature scientific body covering many different disciplines. It has attracted considerable attention because of its capability for representing com plex phenomena and, particularly, for mimicking human reasoning mecha nisms. By moving from classical mathematical models to logical models involving linguistic parameters, fuzzy sets paved the way for emulating human behavior by incorporating imprecision and vagueness. The more the theoretical basis of the field has been developed the greater the number of applications have been foreseen for fuzzy logic. Traditionally, both numerical and algebraic methods have predominated in science and engineering, but many problems have been recognized to be more efficiently handled when we shift from differential-difference equations to fuzzy rules. In particular, the incorporation of these new concepts in control problems has been successfully explored, especially the so-called rule-based fuzzy paradigm. Since the mid-1980s, there has been a growing activity in considering fuzzy models for building controllers. Combining logical operations for the connectives with fuzzy numeric values for the variables and parameters seems very appealing. Furthermore, this unique combination may lead to efficient re sults in practical situations where high numerical precision is neither attainable nor necessary, or where imprecision can provide a robustness that cannot be achieved by classical controllers. Associated with this evolution, electronic implementations of fuzzy con trollers have been reported, and some of them have even gone to production. However, although quite a few examples can be found in the technical litera ture covering a large application area, I personally believe that the practical in corporation of fuzzy techniques into the microelectronics industry is still in its infancy. With the advent of Systems-On-Chip (SOC), the potential usefulness of soft computing in general, and of fuzzy logic in particular, has broadened. There is room to benefit from the advantages offered by fuzzy systems to achieve significant savings in area, power, and cost, as well as improvements in speed, design complexity, and testing effort. In terms of practical realizations, most of the examples given fall into one of two categories: (a) systems based on conventional digital hardware (general- purpose computers) but implementing (in one way or another) fuzzy rules by software and (b) special-purpose circuits (analog, digital, or mixed analog- digital) corresponding to a restricted view of the implementation space. Since there is no universal solution for resolving the huge number of de sign needs a practicing engineer must face, the application of fuzzy logic to
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