Graphical interface aided simulation of speed control of permament magnet synchronous motor with genetic based fuzzy logic controller

It has been shown that fuzzy logic controllers (FLCs) with non-linear structure are one of the control techniques that provide high performance, are robust against parameter variations and are less affected by the disturbances when their design parameters are well adjusted. As the design process of conventional FLC is carried out in accordance with expert knowledge, accuracy and correct application of the provided knowledge are significant problems encountered during the design of FLC. Therefore, the knowledge provided by the expert has important impact on the controller performance. In addition, in such conventional design approaches, the design process takes a long time and optimal control can not be guaranteed. These disadvantages limit the application areas of FLCs.In this thesis, the application of genetic algorithms (GAs) to the design process of FLCs is analyzed. In the original method used, by the help of the multi-objective function defined in terms of the system requirements, scaling coefficients, fuzzy rule table and triangular-type membership functions in the FLC are determined simultaneously. To evaluate the performance of the proposed method, the obtained FLC at the end of the optimization process is applied to the speed control of permanent magnet synchronous motor (PMSM).In the simulation studies realized under constant speed reference/constant load and variable speed reference/variable load working conditions, it has been indicated that the obtained GA-based FLC provide good performance in both transient and steady-state response of the system, though it is evolved in one case.