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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 linear systems. We test the optimal FLC obtained by the genetic algorithms and the PSO applied on linear systems using benchmark plants. The bio-inspired and the evolutionary methods are used to find the parameters of the membership functions of...
In this paper we propose the use of a hybrid PSO-GA optimization method for automatic design of fuzzy logic controllers (FLC) to minimize the steady state error of a plant’s response. We test the optimal FLC obtained by the hybrid PSO-GA method using benchmark control plants. The bio-inspired and the evolutionary methods are used to find the parameters of the membership functions of the FLC to obtain...
In this paper we propose the use of a hybrid PSO-GA optimization method for automatic design of fuzzy logic controllers (FLC). The optimal fuzzy logic controllers are used for the trajectory tracking control of autonomous mobile robots. The bio-inspired and the evolutionary methods are used to find the parameters of the membership functions of the FLC to obtain the optimal controller. Simulation results...
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