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Recursive Weighted ...
Recursive Weighted Null-Space Fitting Method for Identification of Multivariate Systems
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- Fang, Mengyuan (author)
- Zhejiang Sci Tech Univ, Zhejiang Engn Lab Ind Internet Commun Technol, Hangzhou, Peoples R China.;Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang, Peoples R China.
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- Galrinho, Miguel (author)
- OHB Sweden AB, Kista, Sweden.
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- Hjalmarsson, Håkan, 1962- (author)
- KTH,Reglerteknik
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Zhejiang Sci Tech Univ, Zhejiang Engn Lab Ind Internet Commun Technol, Hangzhou, Peoples R China;Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang, Peoples R China. OHB Sweden AB, Kista, Sweden. (creator_code:org_t)
- ELSEVIER, 2021
- 2021
- English.
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In: IFAC PAPERSONLINE. - : ELSEVIER. - 2405-8963. ; , s. 345-350
- Related links:
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https://doi.org/10.1...
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Abstract
Subject headings
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- Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Keyword
- Recursive system identification
- multivariate systems
- weighted null-space fitting
Publication and Content Type
- ref (subject category)
- kon (subject category)
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