The paper investigates the possibilities for applications of genetic algorithms to tuning and optimizing fuzzy controllers, or even to generate fuzzy ...
Modifications of genetic algorithms for designing and optimizing fuzzy ...
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Fine tuning of a fuzzy controller can only be done by careful adjustments of the fuzzy sets in the fuzzy partitions, but not by a change of the rule base.
The paper investigates the possibilities for applications of genetic algorithms to tuning and optimizing fuzzy controllers, or even to generate fuzzy ...
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This method relies on having a set of training data against which the controller is tuned. Recent work has centered on the use of mathematical optimization.
In this paper we apply to Bio-inspired and evolutionary optimization methods to design fuzzy logic controllers (FLC) to minimize the steady state error of ...
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A Genetic Algorithm manipulates the codings representing a parameters set to search a near optimal solution [4], [16], [9]. Because the main design problem of a ...
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural ...
To show the versatility of the methodology, two examples are discussed where GA-optimized fuzzy logic controllers are applied to simulated non-linear plants.
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In this paper, a GA improvement that can speed up convergence and save operation time by neglecting chromosome decoding step is proposed.
This paper describes an enhanced genetic algorithm which constrains the optimization of FLCs to produce well-formed fuzzy sets and rules.
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