永磁同步电机模型预测控制的电流控制策略

Abstract

永磁同步电机(PMSM)的矢量控制受交叉耦合、输出延时、参数失配等因素的影响.针对这些问题,提出了基于模型预测控制(MPC)的电流控制策略.该策略利用MPC的预测状态来减小输出延时对解耦所造成的影响,并使用历史数据进行反馈校正结合滚动优化以消除参数失配和模型误差等因素对控制的影响,保证电流的跟踪性能.仿真和实验结果表明,该策略能够有效地改善矢量控制的动态响应,并具有较强的鲁棒性,此外,该策略的参数整定简单,适合工程应用.

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 was proposed.The predictive states of MPC are used to eliminate the influence that the applying delay has on the decoupling,the feedback correction and receding optimization are implemented based on the foretime information,to eliminate the influence of the factors such as parameter mismatch and model error etc.,so as to guarantee the tracking performance of the current control.The simulation and experimental results demonstrate that the proposed strategy could improve the dynamic response of vector control efficaciously,and has strong robustness.In addition,the parameters are fewer and easy for tuning,which makes it suitable for engineering applications.