Performance analysis of adaptive fuzzy logic controller for switched reluctance motor drive system

This paper presents the application of an adaptive fuzzy algorithm for the speed control of a switched reluctance motor (SRM). The SRM is a highly nonlinear control plant and operates in saturation to maximize the torque output. A systematic approach to the modeling of highly nonlinear SRM drive systems which includes the motor, power converter and its electronic controller is presented. A hysteresis current controlled mid-point power converter is used to feed a 4 kW, four phase, 8/6 pole SRM. Nonlinearity caused by magnetic saturation is accounted for accurate and real-time simulation of drive performance by considering experimental data of magnetization and static torque characteristics. Performance analysis of SRM drives is reported for a with range of operating conditions viz. starting, reversal and load perturbation dynamics. The performance indices of SRM drive system operating with fuzzy logic controller are compared with the conventional controller to highlight the merits and limitations of the adaptive fuzzy logic controller.