Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation
This paper considers the parameter identification problems of the input nonlinear output-error (IN-OE) systems, that is the Hammerstein output-error systems. In order to overcome the excessive calculation amount of the over-parameterization method of the IN-OE systems. Through applying the hierarchi...
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| Published in | Journal of the Franklin Institute Vol. 358; no. 9; pp. 5113 - 5135 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elmsford
Elsevier Ltd
01.06.2021
Elsevier Science Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0016-0032 1879-2693 0016-0032 |
| DOI | 10.1016/j.jfranklin.2021.04.006 |
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| Abstract | This paper considers the parameter identification problems of the input nonlinear output-error (IN-OE) systems, that is the Hammerstein output-error systems. In order to overcome the excessive calculation amount of the over-parameterization method of the IN-OE systems. Through applying the hierarchial identification principle and decomposing the IN-OE system into three subsystems with a smaller number of parameters, we present the key term separation auxiliary model hierarchical gradient-based iterative algorithm and the key term separation auxiliary model hierarchical least squares-based iterative algorithm, which are called the key term separation auxiliary model three-stage gradient-based iterative algorithm and the key term separation auxiliary model three-stage least squares-based iterative algorithm. The comparison of the calculation amount and the simulation analysis indicate that the proposed algorithms are effective. |
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| AbstractList | This paper considers the parameter identification problems of the input nonlinear output-error (IN-OE) systems, that is the Hammerstein output-error systems. In order to overcome the excessive calculation amount of the over-parameterization method of the IN-OE systems. Through applying the hierarchial identification principle and decomposing the IN-OE system into three subsystems with a smaller number of parameters, we present the key term separation auxiliary model hierarchical gradient-based iterative algorithm and the key term separation auxiliary model hierarchical least squares-based iterative algorithm, which are called the key term separation auxiliary model three-stage gradient-based iterative algorithm and the key term separation auxiliary model three-stage least squares-based iterative algorithm. The comparison of the calculation amount and the simulation analysis indicate that the proposed algorithms are effective. |
| Author | Pan, Jian Ding, Feng Yang, Erfu Ma, Hao |
| Author_xml | – sequence: 1 givenname: Feng surname: Ding fullname: Ding, Feng email: fding@jiangnan.edu.cn organization: School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China – sequence: 2 givenname: Hao surname: Ma fullname: Ma, Hao organization: School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China – sequence: 3 givenname: Jian surname: Pan fullname: Pan, Jian organization: School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, PR China – sequence: 4 givenname: Erfu surname: Yang fullname: Yang, Erfu organization: Department of Design, Manufacturing and Engineering Management, University of Strathclyde, Glasgow G1 1XJ, Scotland, UK |
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| Snippet | This paper considers the parameter identification problems of the input nonlinear output-error (IN-OE) systems, that is the Hammerstein output-error systems.... |
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| StartPage | 5113 |
| SubjectTerms | Algorithms Computer simulation Errors Hierarchies Iterative algorithms Iterative methods Least squares Mathematical models Nonlinear equations Nonlinear systems Parameter identification Parameterization Separation Subsystems |
| Title | Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation |
| URI | https://dx.doi.org/10.1016/j.jfranklin.2021.04.006 https://www.proquest.com/docview/2549947549 |
| Volume | 358 |
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