A sliding mode controller for switched-reluctance motor with iterative learning compensation

In this paper, a direct torque sliding mode controller (SMC) is applied to the switched reluctance motor. This controller is robust to load torque and parameter changes. The major problem of sliding mode controller is the chattering in the output which will result in an increase in torque ripples. An iterative learning compensator is proposed to reduce the torque ripple. The iterative learning rule is updated in each iteration. This compensator enhances the performance of the controller to a great extent. The load torque is estimated using a linear Luenberger filter. The simplicity and high performance of the proposed scheme makes it desirable for implementations. The drive achieves satisfactory torque, speed tracking. The functionality of the proposed controller has been tested and verified using simulations.