CSpace  > 系统科学研究所
On input design for regularized LTI system identification: Power-constrained input
Mu, Biqiang1,4; Chen, Tianshi2,3
2018-11-01
Source PublicationAUTOMATICA
ISSN0005-1098
Volume97Pages:327-338
AbstractInput design is an important issue for classical system identification methods but has not been investigated for the kernel-based regularization method (KRM) until very recently. In this paper, we consider the input design problem of KRMs for LTI system identification. Different from the recent result, we adopt a Bayesian perspective and in particular make use of scalar measures (e.g., the A-optimality, D-optimality, and E-optimality) of the Bayesian mean square error matrix as the design criteria subject to power-constraint on the input. Instead of solving the optimization problem directly, we propose a two-step procedure. In the first step, by making suitable assumptions on the unknown input, we construct a quadratic map (transformation) of the input such that the transformed input design problems are convex, and the global minima of the transformed input design problem can thus be found efficiently by applying well-developed convex optimization software packages. In the second step, we derive the characterization of the optimal input based on the global minima found in the first step by solving the inverse image of the quadratic map. In addition, we derive analytic results for some special types of kernels, which provide insights on the input design and also its dependence on the kernel structure. (C) 2018 Elsevier Ltd. All rights reserved.
KeywordInput design Bayesian mean square error Kernel-based regularization LTI system identification Convex optimization
DOI10.1016/j.automatica.2018.08.010
Language英语
Funding ProjectNational Natural Science Foundation of China[61773329] ; National Natural Science Foundation of China[61603379] ; Thousand Youth Talents Plan - central government of China ; Shenzhen Projects - Shenzhen Science and Technology Innovation Council, China[Ji-20170189] ; Shenzhen Projects - Shenzhen Science and Technology Innovation Council, China[Ji-20160207] ; Chinese University of Hong Kong, Shenzhen, China[PF. 01.000249] ; Chinese University of Hong Kong, Shenzhen, China[2014.0003.23] ; Swedish Research Council[20145894] ; National Key Basic Research Program of China (973 Program)[2014CB845301] ; President Fund of Academy of Mathematics and Systems Science, CAS, China[2015-hwyxqnrc-mbq]
WOS Research AreaAutomation & Control Systems ; Engineering
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000447568400038
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/31476
Collection系统科学研究所
Affiliation1.Linkoping Univ, Dept Elect Engn, Div Automat Control, S-58183 Linkoping, Sweden
2.Chinese Univ Hong Kong, Sch Sci & Engn, Shenzhen 518172, Peoples R China
3.Chinese Univ Hong Kong, Shenzhen Res Inst Big Data, Shenzhen 518172, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Mu, Biqiang,Chen, Tianshi. On input design for regularized LTI system identification: Power-constrained input[J]. AUTOMATICA,2018,97:327-338.
APA Mu, Biqiang,&Chen, Tianshi.(2018).On input design for regularized LTI system identification: Power-constrained input.AUTOMATICA,97,327-338.
MLA Mu, Biqiang,et al."On input design for regularized LTI system identification: Power-constrained input".AUTOMATICA 97(2018):327-338.
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, Tianshi]'s Articles
Baidu academic
Similar articles in Baidu academic
[Mu, Biqiang]'s Articles
[Chen, Tianshi]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Mu, Biqiang]'s Articles
[Chen, Tianshi]'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.