Robust Adaptive Fuzzy Sliding Mode Control of Permanent Magnet Stepper Motor with Unknown Parameters and Load Torque

Abstract

In this paper, robust adaptive fuzzy sliding mode control is designed to control the Permanent Magnet (PM) stepper motor in the presence of model uncertainties and disturbances. In doing so, the nonlinear model is converted to canonical form, then, for designing the controller, the robust sliding mode control is designed to decrease the effects of uncertainties and disturbances. A class of fuzzy systems to approximate the ideal input is designed. Stability of closed loop control is also guaranteed by the Lyapunov function employed in controller design. Compared to previous studies that have used position, velocity, and currents phases in the feedback loop to produce and track control signal, the proposed algorithm only needs to measure position and velocity of the shaft for controlling performance of the motor. All the other parameters of motor and load torque are assumed to be unknown. The simulation results show that the control strategy is effective to the motor position tracking error and robust to overcome uncertainties and disturbances..