Abstract
In this article, an optimal Fuzzy PID controller is designed based on genetic optimization for a servo system. For the purpose of the study, an INTECO modular servo system is used in combination with Matlab/Simulink. The proposed controller is with a very simple structure. It uses a one-input fuzzy inference with three rules and six tuning parameters. Also, a conventional fuzzy logic controller with two inputs, 49 rules and three tuning parameters is used. As well a comparison is made with a Standard PID controller. The results of this study show that the system with the synthesized optimal Fuzzy PID controller based on genetic optimization has similar quality characteristics in comparison with the system with a conventional fuzzy PID controller and has a better performance in comparison with a standard PID controller. The use of the genetic algorithm for the synthesis of controller allows a significant reduction in the fuzzy rules base and simple tuning of the controller parameters.
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