A Variable Prediction Horizon Self-Tuning Method for Nonlinear Model Predictive Speed Control on PMSM Rotor Position System

Based on the receding horizon principle, cost function of nonlinear model predictive control (NMPC) becomes an accumulating type to extend prediction horizon. A nonlinear model predictive speed control (NMPSC) with prediction horizon self-tuning method is proposed in this paper, and applied into a permanent magnet synchronous motor (PMSM) rotor position control system with inner-loop of speed. The prediction horizon is improved as a positive integral discrete-time variable which needs to be adjusted according to operating states in each sampling period. Control performances such as rotor position and speed integral of time-weighted absolute value of errors (ITAEs), delay time and calculation burden are compared with the conventional control strategy, and advantages including ITAEs, delay time, weighting factor sensitivities and servo stiffness are obtained. The effectiveness and correctness are verified by simulation and experimental results.