Speed control of permanent magnet synchronous motors using fuzzy controller based on genetic algorithms

Abstract In this study, speed control of a permanent magnet synchronous motor (PMSM) with genetic based fuzzy controller has been simulated. Earlier studies have focused on different components of fuzzy controllers such as rule base or data base in the literature. However, in this study, the whole knowledge base is parameterized and optimized to obtain an optimal fuzzy controller without expert knowledge. In the developed control scheme, there are three closed loops. The two inner loops are the current and the velocity feedbacks, respectively. The other outer feedback is the genetic algorithm (GA) which optimizes the rule base and data base of the fuzzy controller simultaneously. This outer loop is an iterative process. To make comparisons, a conventional fuzzy controller also has been designed and the PMSM speed control has been simulated for both the proposed and conventional fuzzy controller. The comparative results have proved that the proposed controller has a better dynamic response than that of the conventional one.

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