Robust Nonlinear Predictive Controller for Permanent-Magnet Synchronous Motors With an Optimized Cost Function

A robust nonlinear predictive controller for permanent-magnet synchronous motors is proposed. The nonlinear predictive control law is formulated by optimizing a novel cost function. A key feature of the proposed control is that it does not require the knowledge of the external perturbation and parameter uncertainties to enhance the robustness. A zero steady-state error is guaranteed by an integral action of the controller. The stability of the closed-loop system is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified via simulation and experiment. High performance with respect to speed tracking and current control of the motor has been demonstrated.