Design of explicit model predictive control for PMSM drive systems

The performance of current vector control for the permanent magnet synchronous motor (PMSM) is affected by factors such as cross-coupling, applying delay and parameter mismatch. In order to solve these problems, a current control strategy based on the model predictive control (MPC) algorithm is proposed. This strategy uses the prediction state of MPC to reduce the effect of output delay on decoupling. Combining the advantages of MPC with multivariable system and system constraints, it can deal well with the current and voltage limitations in actual systems, and ensure the current tracking performance. In view of the heavy computational burden features of on-line MPC and it is difficult to meet real-time performance in motion control area. In this paper, the Explicit Model Predictive Control (EMPC) is adopted. This method solves the optimization problem through off-line multi-parameter quadratic programming (mp-QP). During real-time operation, it only needs to look up the table according to the current state to obtain the control law with affine form in the current optimization region. The simulation results show that the method satisfies the system constraints and has good dynamic, static and anti-disturbance performance.