Predictive Position Control With System Constraints for PMSM Drives Based on Geometric Optimization

Abstract

The system constraints (current, speed and voltage limitations) are essential for the safety control of predictive position control (PPC) method. However, online solution of model predictive control (MPC) with complex system constraints is still a challenge. In this paper, a novel discrete-time model predictive position control (DMPPC) strategy for surface permanent magnet synchronous motor (SPMSM) drive is proposed, the current, speed and position are regulated simultaneously. The optimization model of the position control system considering system constraints is formulated, the current, speed and voltage constraints are analyzed and transformed into the incremental voltage constraints. To reduce the calculation burden, a simplified method based on the geometric boundaries and cost function is proposed to solve the optimization problem, complex iterative calculations are avoided, the system constraints are well limited and less calculation time can be achieved. Finally, the proposed DMPPC method is experimentally verified and compared with a traditional iterative method and a cascade predictive position control (CPPC) method.