Table Of ContentPlants 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
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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
