Optimal two-vector combination-based model predictive current control with compensation for PMSM drives

ABSTRACT

The duty-ratio-based model predictive control (D-MPC) is rapidly researched for permanent-magnet synchronous machine (PMSM) drives. Existing D-MPC methods produce large current ripple and distortion. To solve this issue and promote the system performance, an optimal two-vector combination MPC (OTC-MPC) is proposed for current control in this paper. The collection of the combination is firstly produced for the proposed OTC-MPC by combining the two vectors and corresponding duty-ratio, and then the optimal combination is selected among all feasible two-vector combinations, thus, the output vectors and duty-ratio are simultaneously optimised. The optimising process is simplified so that the proposed OTC-MPC can be easily implemented. Moreover, a simplified repetitive control with feed-forward compensation method is added to eliminate the predictive current errors of MPC, and also to improve the system robustness against external disturbances. Theoretical analysis, simulation and experimental results demonstrate that the proposed OTC-MPC effectively reduces current ripple and distortion while retaining fast dynamic response compared with the conventional D-MPC.

KEYWORDS:

• Model predictive control (MPC)
• optimal two-vector combination
• feed-forward compensation
• permanent-magnet synchronous machine (PMSM)

Disclosure statement

No potential conflict of interest was reported by the authors.