基于遗传算法的无传感器永磁同步电机控制优化  

Optimization of Sensorless PMSM Controller Based on Genetic Algorithm

作　　者：沈艳霞[1] 江俊[1] 纪志成[1] 

机构地区：[1]江南大学通信与控制工程学院,无锡214122

出　　处：《南京航空航天大学学报》2006年第B07期128-131,共4页Journal of Nanjing University of Aeronautics & Astronautics

基　　金：江苏省高技术研究计划(工业)(BG2005014)资助项目。

摘　　要：基于实数编码遗传算法．实现对无传感器永磁同步电机(PMSM)控制器参数的选取和优化．速度的估计采用扩展卡尔曼滤波(EKF)方法,以PMSM转子速度的测量值与估计值的偏差信号作为遗传算法自适应度求取的依据,实现协方差矩阵中参数的在线调整,节约了系统协方差参数的求取时间,提高了估计器的估计精度。基于dSPACE的快速控制原型工具验证了该方法的有效性。The real-coded genetic algorithm （GA） is adopted to choose and optimize control parameters in the sensorless system of the permanent magnet synchronous motor（PMSM）. The speed is estimated by using the extended Kalman filter （EKF） method. The error between the measured speed and the estimat- ed speed of the PMSM rotor is used as the criterion to compute the adaptive ability, and the parameter in the covariance matrix is adjusted online. Using the method, the computing time is reduced and the estimation precision is improved. A rapid control prototype based on dSPACE is designed to verify the effectiveness of the method.

关 键 词：无传感器控制 遗传算法 永磁同步电机 快速控制原型 

分 类 号：TM341[电气工程—电机]