Predictive Control of Permanent Magnet Synchronous Motor Based on Optimization Model Algorithmic Control

Abstract

This paper presents an optimization model algorithmic control (OMAC) for permanent magnet synchronous motor drive system. The OMAC controller is designed based on the second order ARMA model of permanent magnet synchronous motor. It optimizes the correction coefficient of calculation error and prediction error coefficient of output as well as the amount of the weighting factor in the traditional model algorithmic control. Then selecting only one future time of predictive values to calculate the optimal control law simplifies the calculation process and so overcomes the shortcomings of traditional control needed to select the number of prediction horizon and required to choose a longer sampling period to calculate appropriate control quantity. The algorithm is simple and robustness of the system can be guaranteed. Therefore, the OMAC is well positioned to meet the dynamic and rapid motor real-time requirements. Simulation is conducted to verify the performance of the proposed control scheme.