Speed estimation of PMSM using SRUKF algorithm

2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation

Li, Jingnan^1 ; Gao, Yuan^1 ; Hong, Shuai^1 ; Zhang, Yin^1

School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou

545006, China^1

关键词: Cholesky decomposition;    Convergence and stability;    Nonlinear system equations;    Q R decomposition;    Speed estimation;    Square root unscented Kalman filter;    Truncation errors;    Unscented Kalman Filter;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/5/052013/pdf
DOI  :  10.1088/1757-899X/569/5/052013

来源: IOP

【 摘 要 】

Speed estimation is a key technology to realize sensorless control for the PMSM. Based on the unscented Kalman filter (UKF) method without linearization of nonlinear system equations, this letter provides square root unscented Kalman filter (SRUKF) algorithm that operates through iterating the square roots of the covariance matrixes obtained by QR decomposition and Cholesky decomposition. The presented method can further improve speed estimation performance through decreasing the effect of truncation error and enhancing the convergence and stability of algorithm. Simulation results of sensorless control system demonstrate the feasibility and effectiveness of the proposed algorithm.