Predictive Control of Five-leg Inverter-Double Permanent Magnet Synchronous Motor System with Error Feedback Model

Abstract

In this paper, the five-leg inverter-dual permanent magnet synchronous motor system is taken as the research object. To solve the problem of large steady-state speed fluctuation when applying the traditional model predictive control strategy, based on the mathematical models of the five-leg inverter and the dual permanent magnet synchronous motor, the causes of the fluctuation are analyzed, and then an improved model predictive control algorithm with error feedback is proposed. The algorithm makes full use of the high-speed operation ability of modern digital processor, and introduces the prediction value of error feedback correction model, so that the rolling optimization is not only based on the model, but also makes full use of the actual value of the feedback state variables. At the same time, the second-order Euler discrete method is used to further improve the model progress. Simulation and experimental results show that the model predictive control strategy with error feedback can effectively improve the steady-state speed control performance of the system while maintaining the dynamic performance of the original system and the decoupling control effect of the two motors.