Neuro-fuzzy Compensation of Torque Ripple in a Switched Reluctance Drive

Simple power electronic drive circuit and fault tolerance of converter are specific advantages of SRM drives, but excessive torque ripple has limited its application. This paper presents a novel method of controlling the motor currents to minimize the torque ripple, using a neuro-fuzzy compensator. In the proposed control concept, a compensating signal is added to the output of a classical PI controller, in a current-regulated speed control loop. The compensating signal is learned prior to normal operation, in a self-comissioning run, but the neurofuzzy methodology is also suitable for on-line selflearning implementation, for continuous improvement of the compensating signal.