DocumentCode :
3272844
Title :
Research on a Modified EKF for Speed Estimation in Induction Motor Drives
Author :
Peng, Liu Hai ; Fan, Zhang Qing
Author_Institution :
Shandong Univ., Jinan
fYear :
2007
fDate :
20-24 March 2007
Firstpage :
432
Lastpage :
436
Abstract :
This paper presents and proposes a new approach to resolve the problems of large operation algorithm very short sample time and redundant parameters tuning in induction motor sensorless vector control. The estimation method is based on a long sample time, reduced-order EKF. With this model structure, only the rotor flux components are estimated, besides the rotor speed itself. The new methods predict the rotor speed in the every sample time. So it does not need a short sample time to assume that the differential of speed to be zero. Simulation results show that this new approach can enable us to reduce the execution time of the algorithm without difficulties related to the tuning of covariance matrices and achieve robust speed estimation even in the condition of long sample time.
Keywords :
Kalman filters; control system synthesis; covariance matrices; induction motor drives; machine vector control; parameter estimation; reduced order systems; velocity control; covariance matrices; induction motor drives; induction motor sensorless vector control; modified EKF; reduced-order EKF; robust speed estimation; Artificial neural networks; Convergence; Covariance matrix; Induction motor drives; Induction motors; Machine vector control; Optical feedback; Rotors; Sensor systems; Working environment noise; Extended Kalman Filter; Induction motor; sensorless vector control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Integration Technology, 2007. ICIT '07. IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
1-4244-1092-4
Electronic_ISBN :
1-4244-1092-4
Type :
conf
DOI :
10.1109/ICITECHNOLOGY.2007.4290512
Filename :
4290512
Link To Document :
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