An adaptive sliding self-organizing fuzzy controller for switched reluctance motor drive systems

This paper presents an adaptive sliding self-organizing fuzzy controller (ASSOFC) designed using fuzzy theory and a self-organizing algorithm. Composed of a conventional fuzzy controller (FC) and self-organizing algorithm, the ASSOFC adopts the sliding surface signal as an input, uses the algorithm to adjust the central position of the output consequent membership function of the FC, and, by fuzzy control, regulates the learning rate and fuzzy rules in real time to improve control performance. The ASSOFC is embedded into the direct torque control system of a switched reluctance motor (SRM) as a speed controller, and the performance and feasibility of the controller were validated. The experimental results indicate that the root mean square error values for the ASSOFC at various speed ranges are lower than those for a conventional FC, indicating that the proposed controller provides a superior speed response for SRMs.