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[show abstract]
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ABSTRACT: We present a systematic framework for the stability and design of
nonlinear fuzzy control systems. First we represent a nonlinear plant
with a Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller
design utilizing the concept of so-called “parallel distributed
compensation” is employed. The main idea of the controller design
is to derive each control rule so as to compensate each rule of a fuzzy
system. The design procedure is conceptually simple and natural.
Moreover, the stability analysis and control design problems can be
reduced to linear matrix inequality (LMI) problems. Therefore they can
be solved efficiently in practice by convex programming techniques for
LMIs. The design methodology is illustrated by application to the
problem of modeling and control of a chaotic system-Chua's circuit
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on; 10/1996
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ABSTRACT: In this paper we explore the interaction between fuzzy control
systems and chaos. First we show that fuzzy modeling techniques can be
used to model chaotic dynamical systems. Then we apply some of the newly
developed fuzzy control design techniques to the control of chaotic
systems. The design procedure is conceptually simple, natural and
computationally efficient. Therefore the proposed fuzzy methodology
represents a systematic and effective framework for modeling and control
of chaotic systems. The method is illustrated by application to Chua's
circuits
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on; 06/1996
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[show abstract]
[hide abstract]
ABSTRACT: Presents a design methodology for stabilization of a class of
nonlinear systems. First, the authors represent a nonlinear plant with a
Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller design
utilizing the concept of the so-called “parallel distributed
compensation” is employed. The main idea of the controller design
is to derive each control rule so as to compensate each rule of a fuzzy
system. The design procedure is conceptually simple and natural.
Moreover, the stability analysis and control design problems can be
reduced to linear matrix inequality (LMI) problems. Therefore, they can
be solved efficiently in practice by convex programming techniques for
LMIs. The design methodology is illustrated by application to the
problem of balancing and swing-up of an inverted pendulum on a
cart
IEEE Transactions on Fuzzy Systems 03/1996; · 4.26 Impact Factor
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[show abstract]
[hide abstract]
ABSTRACT: Presents a design methodology for stabilization of a class of
nonlinear systems. First, the authors approximate a nonlinear plant with
a Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller design
utilizing the concept of so-called “parallel distributed
compensation” is employed. The main idea of the controller design
is to derive each control rule so as to compensate each rule of a fuzzy
system. The design procedure is conceptually simple and natural. The
method is illustrated by application to the problem of balancing and
swing-up of an inverted pendulum on a cart
American Control Conference, 1995. Proceedings of the; 07/1995
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[show abstract]
[hide abstract]
ABSTRACT: We present a design methodology for stabilization of a class of
nonlinear systems. First, we approximate a nonlinear plant with a
Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller design
utilizing the concept of so-called “parallel distributed
compensation” is employed. The design procedure is conceptually
simple and straightforward. The method is illustrated by application to
the problem of balancing an inverted pendulum on a cart
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE International Conference on; 04/1995
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IEEE Trans. Fuzzy Syst. 4(1):14-23.
