摘要
用扩展的卡尔曼滤波器(EKF)估计异步电机闭环矢量控制系统中速度变量 /转子磁链的难点是,系统运行的消息噪声和测量噪声模型不易准确获得,而滤波估计的精度和收敛性主要受其影响。为此,提出了一种基于遗传算法(GA)的磁场定向闭环系统噪声协方差全局寻优方法,解决了噪声模型难以辨识的实际问题。仿真结果验证了该方法的有效性。
A problem of closed-loop speed and rotor flux estimation of induction motor with extended Kalman filter (EKF) is its precision and convergence largely depended on the accuracy of the models of system noise and measurement noise which are difficult to identify. Based on genetic algorithms (GA) a global optimized noise covariance estimation method applied to EKF in Field Oriented Control (FOC) system. The simulation results prove the effectiveness and robust of these algorithm.
出处
《电机与控制学报》
EI
CSCD
北大核心
2005年第2期161-165,共5页
Electric Machines and Control
