Design of Adaptive Function Coupling Recurrent Cerebellar Model Articulation Controller for Switched Reluctance Motor Drive Systems

This paper proposes the adaptive functional coupling recurrent cerebellar model articulation controller (AFCRC). The AFCRC system contains an integrated error function, a TSK fuzzy compensator, and a novel cerebellar model articulation controller (CMAC), which is developed based on the concept of a recurrent neural networks (RNNs) and a functional coupling NN (FCNN). This study uses the proposed AFCRC to control the direct torque control drive system of a switched reluctance motor (SRM), and compares it with the traditional CMAC and FCMAC. The experimental results reveal that the root mean square error (RMSE) is used as a performance index for comparing of the traditional CMAC, FCMAC, and AFCRC, respectively. The results show that the proposed AFCRC exhibits the robustness against external disturbances. Thus, the proposed control strategy is advantageous at various speed commands and has improved dynamic responses.