Finite Control Set Model Predictive Control to Guarantee Stability and Robustness for Surface-Mounted PM Synchronous Motors

Abstract

This paper proposes a finite control set model predictive control (FCS-MPC) to guarantee the stability and robustness for surface-mounted permanent magnet synchronous motor (SPMSM) drives. Continuous-input-based control laws are first developed from a control-Lyapunov function in order to both stabilize the closed-loop system via feedback control laws and ensure the robustness via online adaptive laws. Because the asymptotic stability of the proposed control method is guaranteed by at least one discrete switching-state, the continuous-input-based control laws are converted into relevant constraints of the FCS-MPC optimization problem. To validate the advantages of the proposed FCS-MPC, comparative studies with the conventional FCS-MPC and space vector modulation based adaptive control are conducted on a prototype SPMSM testbed with a TI TMS320F28335 DSP. The effectiveness of the proposed FCS-MPC is verified by the comparative schemes with/without the additional constraints. Superiority of the proposed schemes such as zero steady-state error, fast speed-tracking capability, well-regulated stator currents, and low average switching frequency are experimentally validated under the step-changes of load torque and speed reference.