Robust Predictive Torque Control of Permanent Magnet Synchronous Machine Using Discrete Hybrid Prediction Model

Abstract

In the prediction stage of finite control set-predictive torque control for permanent magnet synchronous machine (PMSM), the mismatched parameters will inevitably bring about the predictive errors, which will cause the wrong selection of voltage vector in the optimization stage, and even affect the stability of the entire control system. In order to eliminate the prediction errors, a discrete hybrid prediction model-based predictive torque control (DHPM-PTC) of PMSM is proposed to improve robustness. In the stator current prediction model, the traditional open-loop prediction model is abandoned, and the closed-loop model prediction equation is established. In the stator flux prediction model, this article gets rid of the traditional open-loop integral prediction model, and establishes the closed-loop flux prediction model integrating the current model and the voltage model. Secondly, the stability and parameter design principles of the closed-loop current prediction model and the closed-loop flux prediction model are discussed. Finally, the verification of the proposed algorithm is made on a PMSM test platform. The test results indicate that the proposed DHPM-PTC is superior to the traditional predictive torque control (T-PTC) in dynamic, steady and robust performances.