Development of a Self-Tuning TSK-Fuzzy Speed Control Strategy for Switched Reluctance Motor

This paper presents a novel adaptive Takagi-Sugeno-Kang (TSK)-fuzzy controller (ATSKFC) to regulate the speed of a switched reluctance motor (SRM). The proposed controller comprises two parts: a TSK-fuzzy controller and a compensated controller. The TSK-fuzzy controller is the main controller, which is used to approximate an ideal control law. The compensated controller is designed to compensate the approximation error between the TSK-fuzzy controller and the ideal control law. The parameter variations and the external load of the SRM drive are considered to ensure the robustness of the proposed scheme. An on-line tuning methodology based on Lyapunov is utilized to adjust the parameters of the ATSKFC, so that the stability of the control system can be guaranteed. Three control schemes, ATSKFC, fuzzy control, and PI speed control, are experimentally investigated and the performance index, root-mean-square error, is used to evaluate each scheme. The results reveal that the ATSKFC outperforms other comparison schemes. In addition, the robustness of the proposed scheme to the parameter variations and external load torque disturbance has been verified via simulation and experiments.