EVALUATING GENERALIZED PREDICTIVE CONTROL FOR A BRUSHLESS DC DRIVE

This paper proposes a new control approach for a brushless de motor dr ive using the generalized predictive control (GPC) algorithm. Based on the same least-squares framework as in the controller design, we furt her develop the method to design an observer. The GPC algorithm uses t he receding horizon approach whereby the control signals are determine d by minimizing a quadratic cost function. Our study shows that the ri se time and settling time of the servo system have an approximate line ar relationship with the prediction horizon. Thus, it is used to tune the controller of the drive. Moreover, the control weighting factor ca n be used to smoothe 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.