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Alternative fuzzy controller logics
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, 2002We compare six fuzzy logics used to control a simulated inverted pendulum "plant". Among the six is the standard "Mamdani" fuzzy logic. All systems contain eleven rules and are optimized for fuel economy. Mamdani's logic fares very well in the comparisons, but serious challengers are identified. >
B. Schott, T. Whalen
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2000
The fuzzy set notion enables us to define the progressive membership of an element to a class, that is to say it belongs to this class more or less strongly. The membership of an object in a class defines a degree of membership given between 0 and 1.
Mohand Mokhtari, Michel Marie
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The fuzzy set notion enables us to define the progressive membership of an element to a class, that is to say it belongs to this class more or less strongly. The membership of an object in a class defines a degree of membership given between 0 and 1.
Mohand Mokhtari, Michel Marie
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[1992 Proceedings] IEEE International Conference on Fuzzy Systems, 1992
A systematic design procedure for fuzzy linguistic controllers with adaptive or learning capability is introduced. The design is based on stability and hierarchy of identification and control. The fuzzy rule-base is stored in a fuzzy hypercube and the fuzzy control action is computed via a fuzzy inference mechanism.
H. Kang, G. Vachtsevanos
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A systematic design procedure for fuzzy linguistic controllers with adaptive or learning capability is introduced. The design is based on stability and hierarchy of identification and control. The fuzzy rule-base is stored in a fuzzy hypercube and the fuzzy control action is computed via a fuzzy inference mechanism.
H. Kang, G. Vachtsevanos
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1992
Fuzzy Set Theory, introduced by Zadeh in 1965 [77], has been the subject of much controversy and debate. In recent years, it has found many applications in a variety of fields. Among the most successful applications of this theory has been the area of Fuzzy Logic Control (FLC) initiated by the work of Mamdani and Assilian [36]. FLC has had considerable
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Fuzzy Set Theory, introduced by Zadeh in 1965 [77], has been the subject of much controversy and debate. In recent years, it has found many applications in a variety of fields. Among the most successful applications of this theory has been the area of Fuzzy Logic Control (FLC) initiated by the work of Mamdani and Assilian [36]. FLC has had considerable
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FUZZY LOGIC FOR CONTROL SYSTEMS
IFAC Proceedings Volumes, 1992Abstract Ever since fuzzy set theory was first proposed by Professor Zadeh, People in the control field have examined very carefully its applicability to the real world. Very few results of practical application were reported namely due to the difficulty of proving validity.
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Genetic fuzzy logic controllers
Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems, 2003The conventional fuzzy logic controller (CFLC) is limited in application, because its logic rules and membership functions have to be preset with expert knowledge. To avoid such drawbacks, a genetic fuzzy logic controller (GFLC) is proposed by employing an iterative evolution algorithm to promote the learning performance of logic rules and the tuning ...
null Yu-Chiun Chiou, L.W. Lan
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2021
We consider a simple fuzzy logic control methodology that is applicable for most systems. It was proven and utilized for the first time in renewable energy systems and wind turbine control systems. We also look at fuzzy control preliminaries, fuzzy controller heuristics, fuzzy logic controller design, and industrial fuzzy control supervision and ...
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We consider a simple fuzzy logic control methodology that is applicable for most systems. It was proven and utilized for the first time in renewable energy systems and wind turbine control systems. We also look at fuzzy control preliminaries, fuzzy controller heuristics, fuzzy logic controller design, and industrial fuzzy control supervision and ...
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Fuzzy logic process controller
IEEE International Conference on Systems Engineering, 2002The application of a hierarchical structure for the design of a fuzzy logic process controller is described. With this hierarchical structure, the number of rules constituting a fuzzy controller will increase linearly and not exponentially with the number of system variables.
G.V.S. Raju, J. Zhou
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2020
The term fuzzy logic has been used in two different senses. It is thus important to clarify the distinctions between these two different usages of the term. In a narrow sense, fuzzy logic refers to a logical system that generalizes classical two-valued logic for reasoning under uncertainty.
Piush Kumar, Sarika Shrivastava
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The term fuzzy logic has been used in two different senses. It is thus important to clarify the distinctions between these two different usages of the term. In a narrow sense, fuzzy logic refers to a logical system that generalizes classical two-valued logic for reasoning under uncertainty.
Piush Kumar, Sarika Shrivastava
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1989
In this chapter we review previous results in the effort to incorporate approximate reasoning into the control of physical processes. In particular, we wish to review the research in fuzzy logic control and show how the research presented here is a logical extension of that work.
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In this chapter we review previous results in the effort to incorporate approximate reasoning into the control of physical processes. In particular, we wish to review the research in fuzzy logic control and show how the research presented here is a logical extension of that work.
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