New genetic-based design of a Pi-like fuzzy logic speed controller for an induction motor

The design methods of fuzzy logic controllers (FLCs) using the genetic/evolutionary algorithms (GEAs) are appearing as systematic methods. These methods easily provide an optimized design and form the framework for further progress. This paper describes the design of P-, PI-, PD-, PID-like FLCs based on theoretical fuzzy concepts and genetic-based optimization. In PI-like FLC, the most important feature of the proposed controller is its simple structure consisting of three gain factors associated with a FLC with each of the two inputs and the output has only three membership functions. Through GEAs, the optimal values for the gain factors associated with each of the inputs and the output of the FLC are achieved without changing the membership functions or the rule-base of the FLC itself. The proposed method is applied to the problem of designing a PI-like fuzzy logic speed controller for an induction motor. The performance of the compensated system is judged compared to that of conventional PI controller. Simulation results obtained using the proposed method showed better control performance in handling plant parameter changes, disturbance signals, and in speeding up the response.