Nonlinear Predictive Control of Interior Permanent Magnet Synchronous Machine with Extra Current Constraint

Abstract

The interior permanent magnet synchronous machine (IPMSM) has been widely used in industrial applications due to its several favorable advantages. To further improve the machine performance, an improved nonlinear predictive controller for the IPMSM is proposed. In this paper, the maximum torque per ampere control law is firstly transformed to a linear function, according to the first−order Taylor expansion, and integrated with the control strategy. On this basis, an improved predictive control method is formulated by designing an optimized cost function through the input−output feedback linearization. Then the integral action is introduced to eliminate the influence of the load mutation and improve the steady−state control precision of the system. The stability of the control method is ensured by compelling the outputs to track the desired references without steady−state error. Finally, the simulation was established to verify the effective of the improved control method. Simulation results showed that the machine can reach the given reference speed without steady−state error within a short process, which means the machine has excellent dynamic and static performances. Furthermore, the machine has higher torque−to−current ratio by making full use of the reluctance torque. The simulation results verify the effectiveness of the improved control strategy.