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《Journal of Chongqing University of Technology(Natural Science)》 2011-01
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Study of Adaptive Identification Methods for Time-variant Parameters of Direct Current Motors

DONG Chao-yi,CHEN Xiao-Yan (College of Electric Power,Inner Mongolia University of Technonlogy,Huhhot 010110,China)  
The parameters of a direct current motor model are often influenced by operation environments or working conditions and are imprecise.To solve this problem,this paper studies and compares the performances of five methods: Recursive Least Squares(RLS),Recursive Least Squares with Exponential Forgetting(RLSEF),Recursive Least Squares with Matrix Regularization(RLSMR),Projection Algorithm(PA) and Normalized Least Mean Square(NLMS).Four error integration criteria(ISE,ITSE,IAE,ITAE) are used to test and evaluate the precisions of the real-time estimations.The simulations show that RLSEF method has an optimal precision of parameter estimations.
【Fund】: 内蒙古自治区教育厅自然科学研究重点项目(NJ10070);; 内蒙古工业大学校基金资助项目(X20416) 内蒙古工业大学校基金资助项目(X200805)
【CateGory Index】: TM33
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