Fuzzy logic rotor position estimation based switched reluctance motor DSP drive with accuracy enhancement

This paper describes a novel angle estimation scheme for a real time digital signal processor (DSP) based switched reluctance motor drive using fuzzy logic where several unique techniques are implemented to improve the estimation accuracy. First, an optimized fuzzy model of the motor was created using an adaptive neuro-fuzzy inference system (ANFIS) based on accurately measured flux linkage data. Secondly, an improved fuzzy optimal sensing phase selector was developed based on the analysis of both modeling error and measurement error. Lastly, a delayless polynomial predictive filter and an online phase winding resistance estimator are also implemented to further improve the position estimation accuracy. Both simulation and experiment results on a DSP based real time drive are presented to show the effectiveness of this scheme.