A Novel Case of Practical Exponential Observer Using Extended Kalman Filter

doi:10.1109/ACCESS.2018.2870491

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	A Novel Case of Practical Exponential Observer Using Extended Kalman Filter
	Ji, Daxiong 1; Deng, Zhi 1; Li, Shuo2 ; Ma, Dongfang 1; Wang, Tao 1; Song, Wei 1; Zhu, Shiqiang 1; Wang, Zhi 3; Pan, Hongjun 4; Sharma, Sanjay 5; Yang, Xu6
发表期刊	IEEE ACCESS
ISSN	2169-3536
	2018
卷号	6 页码:58004-58011
通讯作者	Ji, Daxiong(jidaxiong@zju.edu.cn)
摘要	This technical note presents a case of practical exponential observer using extended Kalman filter (EKF) independent of certain restrictions, such as online check and estimation error of initial state. Recursive state estimation is usually a challenge for discrete-time nonlinear system in terms of computation cost. EKF is attractive with its simplicity since it is considered as an exponential observer given the above restrictions. However, those restrictions are so mathematically complicated that EKF cannot be practical in estimation. A novel case for an exponential observer using EKF is proposed, which is independent of such restrictions. However, these restrictions are proved to be unnecessary in the case. The proposed case is illustrated by a navigation system scenario. The validity of the case is demonstrated by a numerical simulation experiment. The system is deterministic.
关键词	Discrete-time nonlinear system extended Kalman filter exponential observer restrictions spectral norm
DOI	10.1109/ACCESS.2018.2870491
关键词[WOS]	STATE ESTIMATION ; COOPERATIVE NETWORKS ; NONLINEAR ESTIMATION ; SYSTEMS ; TRACKING
收录类别	SCI
语种	英语
资助项目	U.K. Royal Society-International Exchanges 2017 Cost Share, China[IEC\NSFC\170405] ; Fundamental Research Funds for the Central Universities ; National Key Research and Development Program of China[2016YFC0300801] ; National Natural Science Foundation of China[51679213] ; National Natural Science Foundation of China[51679213] ; National Key Research and Development Program of China[2016YFC0300801] ; Fundamental Research Funds for the Central Universities ; U.K. Royal Society-International Exchanges 2017 Cost Share, China[IEC\NSFC\170405]
项目资助者	National Natural Science Foundation of China ; National Key Research and Development Program of China ; Fundamental Research Funds for the Central Universities ; U.K. Royal Society-International Exchanges 2017 Cost Share, China
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000449002100001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/22831
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Ji, Daxiong
作者单位	1.Zhejiang Univ, Ocean Coll, Key Lab Ocean Observat Imaging Testbed Zhejiang P, Zhoushan 316000, Peoples R China 2.Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110000, Liaoning, Peoples R China 3.Zhejiang Univ, Coll Control Sci & Engn, Zhoushan 316000, Peoples R China 4.Zhejiang Ocean Univ, Sch Math Phys & Informat Sci, Zhoushan 316000, Peoples R China 5.Plymouth Univ, Sch Engn, Plymouth PL4 8AA, Devon, England 6.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Ji, Daxiong,Deng, Zhi,Li, Shuo,et al. A Novel Case of Practical Exponential Observer Using Extended Kalman Filter[J]. IEEE ACCESS,2018,6:58004-58011.
APA	Ji, Daxiong.,Deng, Zhi.,Li, Shuo.,Ma, Dongfang.,Wang, Tao.,...&Yang, Xu.(2018).A Novel Case of Practical Exponential Observer Using Extended Kalman Filter.IEEE ACCESS,6,58004-58011.
MLA	Ji, Daxiong,et al."A Novel Case of Practical Exponential Observer Using Extended Kalman Filter".IEEE ACCESS 6(2018):58004-58011.