Predictive Tracking Control of Planar Switched Reluctance Motors Using Predictive-Position-Error-Feedback Compensation

A position tracking control method derived from model predictive control theory is propounded to achieve higher position tracking accuracy of planar switched reluctance motor (PSRMs). The machine model of the laboratory PSRM is given and the dynamic model of the PSRM is expressed by discrete-state-space form. Relying on the established dynamic model, the PSRM model predictive position controller (MPPC) is constructed. In addition, a proportional-integral-differential (PID) compensator is developed to decrease the position difference by feedback from the predictive position and the actual position, because MPPC only makes the predicted position close to the reference position. The control action of PSRM is obtained by the output combination of compensator and model predictive position controller. The simulation results show that the MPPC with the compensator can effectively improve the position tracking accuracy compared to the MPPC without the compensator.