DocumentCode
3208878
Title
Research on adaptive identification methods for time-variant parameters of rare earth brushless DC motors
Author
Xiaowei Sun ; Su Li ; Peng Li ; Xinling Shi ; Shuang Hu
Author_Institution
Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming, China
fYear
2015
fDate
23-25 May 2015
Firstpage
6472
Lastpage
6475
Abstract
The parameters of brushless DC motor are not stable under complicated conditions which can lead to modeling imprecision problem. To solve this problem, this paper presents a real-time tracking method of Recursive Least Squares algorithm to improve the influence of motor parameters to the operation qualities. In order to accurately establish the motor model and validate the effectiveness of this method, this paper use the method of Recursive Least Squares algorithm to identify the on-line system of rare earth permanent magnet brushless DC motor. The result indicates that the parameters identification method can reduce computation complexity and simulate dynamic system accurately.
Keywords
brushless DC motors; least squares approximations; parameter estimation; recursive estimation; adaptive identification methods; parameters identification method; rare earth permanent magnet brushless DC motor; real-time tracking method; recursive least squares algorithm; time-variant parameters; Brushless DC motors; Heuristic algorithms; Hysteresis motors; Parameter estimation; Permanent magnet motors; Recursive Least Squares (RLS); on-line identification; rare earth permanent magnet DC motor; real-time tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7161984
Filename
7161984
Link To Document