CSpace  > 系统科学研究所
Recursive Identification of Hammerstein Systems: Convergence Rate and Asymptotic Normality
Mu, Biqiang1; Chen, Han-Fu1; Wang, Le Yi2; Yin, George3; Zheng, Wei Xing4
2017-07-01
Source PublicationIEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN0018-9286
Volume62Issue:7Pages:3277-3292
AbstractIn this work, recursive identification algorithms are developed for Hammerstein systems under the conditions considerably weaker than those in the existing literature. For example, orders of linear subsystems may be unknown and no specific conditions are imposed on their moving average part. The recursive algorithms for estimating both linear and nonlinear parts are based on stochastic approximation and kernel functions. Almost sure convergence and strong convergence rates are derived for all estimates. In addition, the asymptotic normality of the estimates for the nonlinear part is also established. The nonlinearity considered in the paper is more general than those discussed in the previous papers. A numerical example verifies the theoretical analysis with simulation results.
KeywordAsymptotic normality Hammerstein system kernel function nonparametric approach recursive estimation stochastic approximation strong consistency
DOI10.1109/TAC.2016.2629668
Language英语
Funding ProjectNational Key Basic Research Program of China (973 program)[2014CB845301] ; National Natural Science Foundation of China[61603379] ; National Natural Science Foundation of China[61273193] ; National Natural Science Foundation of China[61120106011] ; National Natural Science Foundation of China[61134013] ; President Fund of Academy of Mathematics and Systems Science, CAS[2015-hwyxqnrc-mbq] ; Air Force Office of Scientific Research[FA9550-15-1-0131] ; Australian Research Council[DP120104986]
WOS Research AreaAutomation & Control Systems ; Engineering
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000404299300013
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/25797
Collection系统科学研究所
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control CAS, Beijing 100190, Peoples R China
2.Wayne State Univ, Dept Elect & Comp Engn, Detroit, MI 48202 USA
3.Wayne State Univ, Dept Math, Detroit, MI 48202 USA
4.Univ Western Sydney, Sch Comp Engn & Math, Sydney, NSW 2751, Australia
Recommended Citation
GB/T 7714
Mu, Biqiang,Chen, Han-Fu,Wang, Le Yi,et al. Recursive Identification of Hammerstein Systems: Convergence Rate and Asymptotic Normality[J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL,2017,62(7):3277-3292.
APA Mu, Biqiang,Chen, Han-Fu,Wang, Le Yi,Yin, George,&Zheng, Wei Xing.(2017).Recursive Identification of Hammerstein Systems: Convergence Rate and Asymptotic Normality.IEEE TRANSACTIONS ON AUTOMATIC CONTROL,62(7),3277-3292.
MLA Mu, Biqiang,et al."Recursive Identification of Hammerstein Systems: Convergence Rate and Asymptotic Normality".IEEE TRANSACTIONS ON AUTOMATIC CONTROL 62.7(2017):3277-3292.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Mu, Biqiang]'s Articles
[Chen, Han-Fu]'s Articles
[Wang, Le Yi]'s Articles
Baidu academic
Similar articles in Baidu academic
[Mu, Biqiang]'s Articles
[Chen, Han-Fu]'s Articles
[Wang, Le Yi]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Mu, Biqiang]'s Articles
[Chen, Han-Fu]'s Articles
[Wang, Le Yi]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.