摘要
为实现模型预测控制算法在永磁同步电机控制中的应用,本文提出了永磁同步电机递推模型预测控制方法,利用计算量较小的递推过程替代迭代过程。首先,采用迭代学习控制并利用有限信息求取操作变量第一项。随后采用递推Levenbei Marquardt算法求出操作变量其它项。为说明提出算法的有效性,分别计算了MPC和RMPC算法的时间复杂度,并分析了递推MPC的收敛性。最后,对递推模型预测算法的有效性进行了仿真验证。
To apply MPC in PMSM control system, a recursive MPC （ RMPC ） algorithm was proposed in this paper. An optimization problem was required to solve online by way of iteration in MPC, which has heavy computational burden. Thus, iteration was replaced by recursion which need less computation in the paper. In RMPC, iterative learning control （ILC） was used to obtain the first term of manipulated variables, and then recursive Levenberg Marquardt algorithm was adopted to solve the online optimization problem. The convergency of RLMA was analysed. Furthermore, to testify that RMPC has less computational burden, time complexity of MPC and RMPC were computed. Simulation results show the effectiveness of proposed method.
出处
《微电机》
2015年第7期54-59,共6页
Micromotors
关键词
永磁同步电机
模型预测控制
递推算法
迭代算法
permanent magnet synchronous motor
model predictive control
recursion algorithm
iteration algorithm
