A current regulator for model predictive control based on Laguerre function applied for permanent magnet synchronous motor

Abstract

Because of the complex operation conditions of permanent magnet synchronous motor, the motor parameter changes, and traditional synchronous PI control performance is not very satisfactory. Current regulator based on complex vector PI control improves the control effect to some extent, but there is still the problem of long response time and large overshoot. Therefore, a LMPC current regulator is designed for permanent magnet synchronous motor controller. This kind of current regulator obtains optimal control law through multistep prediction on the state quantity of system according to the past and present information, and in overall consideration of changes in predicted value and control quantity of the controlled object and other evaluating indicators. Simulation and experimental results show that, this kind regulator has faster dynamic response and better parametric robustness, as compared to the traditional synchronous PI and complex vector PI control.