onextendedstatebasedkalmanfilterdesignforaclassofnonlineartimevaryinguncertainsystems

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	onextendedstatebasedkalmanfilterdesignforaclassofnonlineartimevaryinguncertainsystems
	Bai Wenyan 2; Xue Wenchao1 ; Huang Yi1 ; Fang Haitao1
刊名	sciencechinainformationscience
	2018
卷号	061 期号:004 页码:042201
ISSN号	1674-733X
英文摘要	This paper considers the filtering problem for a class of multi-input multi-output systems with nonlinear time-varying uncertain dynamics, random process and measurement noise. An extended state based Kalman filter, with the idea of timely estimating the unknown dynamics, is proposed for better robustness and higher estimation precision. The stability of the proposed filter is rigorously proved for nonlinear timevarying uncertain system with weaker stability condition than the extended Kalman filter, i.e., the initial estimation error, the uncertain dynamics and the noises are only required to be bounded rather than small enough. Moreover, quantitative precision of the proposed filter is theoretically evaluated. The proposed algorithm is proved to be the asymptotic unbiased minimum variance filter for constant uncertainty. The simulation results of some benchmark examples demonstrate the feasibility and effectiveness of the method.
语种	英语
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/43701]
专题	系统科学研究所
作者单位	1.中国科学院数学与系统科学研究院 2.Beijing Aerospace Automatic Control Institute
推荐引用方式 GB/T 7714	Bai Wenyan,Xue Wenchao,Huang Yi,et al. onextendedstatebasedkalmanfilterdesignforaclassofnonlineartimevaryinguncertainsystems[J]. sciencechinainformationscience,2018,061(004):042201.
APA	Bai Wenyan,Xue Wenchao,Huang Yi,&Fang Haitao.(2018).onextendedstatebasedkalmanfilterdesignforaclassofnonlineartimevaryinguncertainsystems.sciencechinainformationscience,061(004),042201.
MLA	Bai Wenyan,et al."onextendedstatebasedkalmanfilterdesignforaclassofnonlineartimevaryinguncertainsystems".sciencechinainformationscience 061.004(2018):042201.