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
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;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7161984