Control of Switched Reluctance Motor Using Model Predictive Controller

Amadi Christian Sunday, D. O. Aborisade, I. G. Adebayo

Abstract


Switched Reluctance Motors (SRMs) have gained prominence in variable speed and electric propulsion applications due to their significant advantages. However, due to parameter variations and intricacies of phase commutation of the SRM, achieving optimal speed control on load tongue variation has posed a great challenge to its speed control. The existing Proportional Integral Derivative (PID) controllers have been employed by researchers to regulate the speed and torque of various motors. Still, their effectiveness is hindered by the non-linear nature of SRMs and the associated parameter variations. Therefore, this study dealt with speed control of SRM using a Model Predictive Controller (MPC) to achieve dynamic control performance under diverse operating conditions. The mathematical model of the SRM was formulated based on its electromechanical tongue characteristics. A Model Predictive Control (MPC) strategy was developed based on the formulated SRM model to achieve speed control. The model was simulated to control SRM using MATLAB 2020Ra Simulink environment. The performance evaluation of the suggested MPC model was done using rise time, percentage overshoot, and settling time as metrics, and the comparison was carried out with the conventional PID controller. The rise time, settling time, and percentage overshoot obtained for the model predictive controller were 4.38 seconds, 2.17 seconds, and 13.44%, respectively. The rise time, settling time, and percentage overshot obtained for the PID controller were 1.16 seconds, 19.47 seconds, and 36.86%, respectively. The outcome of this study showed that the MPC controller performed better in terms of percentage overshot and settling time as compared with that of the conventional PID controller. The Model Predictive Controller (MPC) can be useful in a chemical plant for temperature, pressure, flow, and composition control.


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