期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 15, 期 2, 页码 650-662出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2018.2810850
关键词
Cholesky triangular decomposition; fading factors; induction motor (IM); real-time speed identification; strong tracking extended Kalman filter (STEKF)
类别
资金
- National Natural Science Foundation of China [51677150]
- Specialized Research Fund of Shaan Xi Province [2015KJXX-29]
- State Key Laboratory of Large Electric Drive System and Equipment Technology [SKLLDJ012016006]
This paper proposes a real-time speed identification method by using a symmetric strong tracking extended Kalman filter (SSTEKF) for induction motor sensorless drive. In SSTEKF, the residual sequences are forced orthogonal to each other, and the gain matrix is tuned in real-time by introducing fading factors into the covariance matrix of the predicted state. The modeling error is reduced, and the mutational state is tracked rapidly based on SSTEKF. Simultaneously, the Cholesky triangular decomposition is used to change the working way of the multiple fading factor matrix in the error covariance matrix. The application of the Cholesky triangular decomposition guarantees that the error covariance matrix is symmetric in the process of iteration, and the stability of the algorithm is enhanced. Therefore, the estimation accuracy, the tracking speed, and the noise suppression of the proposed method are better than the EKF. The correctness and effectiveness of the proposed method are verified by experimental results.
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