Abstract：The performance of direct torque control (DTC) for induction motor is depended on the stator flux estimation in a large degree. Extended Kalman filter (EKF) is useful to estimate state variables when the measured signal is mixed with noise. A flux linkage flux estimation method for induction motor based on EKF theory is presented in this paper, where, the stator current, stator resistance as well as linkage flux are regarded as the state variables to be estimated by joint filtering. For the sake of improving the accuracy of the filtering, genetic algorithm (GA) is introduced to optimize the noise matrix in EKF. The closed loop system composed by DTC controller and the proposed linkage flux observer with optimized filtering parameter has better estimating accuracy and dynamic low speed performance than ordinary EKF-DTC scheme. The effectiveness is verified by simulation and experimental results.
张勇军, 王京, 李华德. 基于遗传算法优化的定子磁链扩展卡尔曼估计方法[J]. 电工技术学报, 2009, 24(9): 64-70.
Zhang Yongjun, Wang Jing, Li Huade. A Method of the Stator Flux EKF Estimation for Induction Motors Based on Genetic Algorithm Optimizing. Transactions of China Electrotechnical Society, 2009, 24(9): 64-70.
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