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	Normalized residuals based strong tracking filter and its application
	Liu Ming ; Zhou Dong-hua
	2010-05-06 ; 2010-05-06
关键词	Practical Theoretical or Mathematical/ fault diagnosis filters nonlinear systems power electronics/ normalized residuals strong tracking filter nonlinear systems multioutput systems fault diagnosis residuals normalization/ B1270 Filters and other networks
中文摘要	The strong tracking filter (STF) can reduce adaptively estimate bias and thus has ability to track abrupt changes in nonlinear systems. When large difference exists among the system outputs in multi-output systems, the difference among residuals are also large when no fault occurs. This difference lead to information asymmetry in the filter residuals, and the speed and precision is damaged. In this paper a residuals-normalized STF method is presented. In this method the residuals are normalized when computing the suboptimal fading factors. So the information of the residuals is balanced. Simulation results show that the speed and precision of fault diagnosis can be improved by use of this improved filter.
语种	英语 ; 英语
出版者	Chinese Soc. Electr. Eng ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9584]
专题	清华大学
推荐引用方式 GB/T 7714	Liu Ming,Zhou Dong-hua. Normalized residuals based strong tracking filter and its application[J],2010, 2010.
APA	Liu Ming,&Zhou Dong-hua.(2010).Normalized residuals based strong tracking filter and its application..
MLA	Liu Ming,et al."Normalized residuals based strong tracking filter and its application".(2010).

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