基于并行混沌优化算法的永磁同步电机多参数辨识

Multi Parameter Identification of PMSM Based on Parallel Chaos Optimization Algorithm

为提高永磁同步电机(PMSM)系统多参数辨识的精度,实现PMSM的高性能控制,研究了一种并行混沌优化算法。针对一些PMSM多参数辨识方法由于数学模型欠秩问题而导致辨识结果的不确定性以及混沌优化算法对初始值敏感的缺陷,将并行混沌优化算法应用到PMSM多参数辨识中。分别采集在实际PMSM模型i d=0和i d≠0控制条件下的数据,从而构建PMSM四阶d,q模型,解决了状态方程辨识电机多个参数时存在的欠秩问题;确定合适的并行数,从多个初始值同时出发进行全局搜索,克服了混沌优化算法对于初始值敏感、易陷入局部最优的缺陷;根据目标函数值,得到PMSM参数辨识的最优结果。该方法可满足在同一PMSM四阶模型中对定子电阻、d,q轴电感和永磁体磁链进行辨识。通过仿真实验进行验证,该算法相比较混沌优化算法具有稳定性好,收敛速度快,辨识效率、精度较高的优点。

In order to improve the accuracy of multi parameter identification of permanent magnet synchronous motor(PMSM)system and realize the high performance control of PMSM,a parallel chaos optimization algorithm was proposed in this paper.The parallel chaos optimization algorithm was applied to the multi parameter identification of PMSM.The real PMSM model and the real PMSM model were collected respectively,the fourth-order d-q model of PMSM was built based on the data under the control condition of i d=0 and i d≠0.It solves the problem of under rank when the state equation identifies multiple parameters of the motor.The appropriate parallel number was determined.The global search was carried out from multiple initial values at the same time.It overcomes the defect that the chaos optimization algorithm is sensitive to the initial value and easy to fall into the local optimum.According to the objective function value,the PMSM parameters were obtained The optimal result of number identification.The method can be used to identify stator resistance,d,q axis inductance and permanent flux in the same PMSM fourth-order model.Compared with chaos optimization algorithm,this algorithm has the advantages of good stability,fast convergence speed,high identification efficiency and accuracy.