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

Robust cascaded nonlinear predictive control of a permanent magnet synchronous motor with antiwindup compensator

A nonlinear predictive control (NPC) scheme in a cascaded structure for a permanent magnet synchronous motor drive is proposed. Taylor series expansion is used to predict the system response over a finite horizon. As NPC cannot remove completely the steady-state error in the presence of mismatched parameters and external perturbation, a disturbance observer is used to estimate the offset caused by parametric uncertainties and the load torque variation. In addition, input constraints (restrictions on the magnitude) are considered in the synthesis of the disturbance observer, resulting in an equivalent cascaded proportional integral action with an antiwindup compensator. The validity of the proposed controller was tested via simulation and experiment. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection