Single rate and multirate predictive control of a brushless DC drive

This thesis proposes a new control approach to control the position of a brushless DC motor drive using the state space generalized predictive control (GPC) algorithm. The basic idea of the GPC is to calculate a sequence of current and future control signals that minimises a cost function based on predictions of the plant output, setpoint and the available information. The aim of the thesis is to determine a tuning process for the application of GPC to the motor drive. Hence, the effect of the motor and the controller parameters on the performance and the robustness of the drive is examined. The study shows that the rise time and settling time of the servo system have an approximate linear relationship with the prediction horizon. Therefore, it is used to tune the controller of the drive. Also, the study shows that the control weighting factor can be used to smoothen the controller output. In motion control, the mismatch of the actual and nominal motor inertia readily affects the performance and robustness of the drive. In most applications, the exact load inertia is unknown. To design the controller, the study shows that with proper selection of prediction horizon and the nominal inertia used in the design, we can achieve a reasonable performance and robustness.Master of Engineerin