A parameter-optimized analytic fuzzy controller based on a genetic algorithm

摘要

A fuzzy controller based on analytic rules, which can self-adjust the fuzzy rules online, has good performance. That can change the output of the controller by modifying the fuzzy rules. An improved structure of a fuzzy controller based on analytic rules was proposed, and a modifying function aiming to regulate the fuzzy rules dynamically was introduced. The novel approach can effectively alleviate the contradictions between speediness and overshoot. Moreover, the genetic algorithm was applied to optimize five parameters of the fuzzy controller simultaneously. The steps required in seeking optimized parameters are presented. Simulation was conducted to show the efficiency of the proposed approach.