Evaluating generalized predictive control for a brushless DC drive

This paper proposes a new control approach for a brushless DC motor drive using the generalized predictive control (GPC) algorithm. Based on the same least-squares framework as in the controller design, we further develop the method to design an observer. The GPC algorithm uses the receding horizon approach whereby the control signals are determined by minimizing a quadratic cost function. Our study shows that the rise time and settling time of the servo system have an approximate linear relationship with the prediction horizon. Thus, it is used to tune the controller of the drive. Moreover, the control weighting factor can be used to smooth the controller output. The proposed algorithm has been implemented using a digital signal processor (DSP) and tested in real time with a prototype system. The performance and robustness of the algorithms have been evaluated both in simulation and experiment. The results show that the drive performs reasonably well despite load changes and step changes in the position setpoint. Furthermore, it is fairly robust against motor parameters change.