Iterative parameter identification algorithms for transformed dynamic rational fraction input-output systems

被引:44
作者
Miao, Guangqin [1 ]
Ding, Feng [1 ]
Liu, Qinyao [2 ]
Yang, Erfu [3 ]
机构
[1] Jiangnan Univ, Sch Internet Things Engn, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China
[2] Xian Jiaotong Liverpool Univ, Dept Mechatron & Robot, Suzhou 215123, Peoples R China
[3] Univ Strathclyde, Dept Design Mfg & Engn Management, Glasgow G1 1XJ, Scotland
基金
中国国家自然科学基金;
关键词
Rational fraction system; Gradient search; Newton search; Model transformation; Parameter identification; FAULT-DIAGNOSIS; MODEL; OPTIMIZATION; ESTIMATOR; SELECTION; TRACKING; DELAY;
D O I
10.1016/j.cam.2023.115297
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The rational fraction system is a special nonlinear system, the existence of the denomi-nator polynomial leads to the difficulty of identifying rational fraction models. Inspired by the gradient search and the Newton method, the gradient-based iterative algorithm and Newton iterative algorithm are presented to estimate the parameters of rational fraction system models. Furthermore, in order to avoid a large amount of calculation and complex equations encountered in the process of solving partial derivatives, the model transformation-based gradient iterative algorithm and the model transformation-based Newton iterative algorithm are proposed for parameter identification. Two examples are carried out to show the effectiveness of the proposed algorithms. This paper focuses on solving the identification problem of rational fraction systems. (c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数:23
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