Two-stage parameter estimation methods for linear time-invariant continuous-time systems

被引:1
作者
Ding, Feng [1 ,2 ,6 ]
Xu, Ling [3 ,7 ]
Liu, Peng [4 ]
Wang, Xianfang [5 ]
机构
[1] Wuhan Donghu Univ, Sch Elect & Informat Engn, Wuhan 430212, Peoples R China
[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China
[3] Changzhou Univ, Sch Microelect & Control Engn, Changzhou 213159, Peoples R China
[4] North Univ China, Sch Elect & Control Engn, Taiyuan 030051, Peoples R China
[5] Henan Inst Technol, Sch Comp Sci & Technol, Xinxiang 453003, Peoples R China
[6] Qingdao Univ Sci & Technol, Coll Automat & Elect Engn, Qingdao 266061, Peoples R China
[7] Hubei Univ Technol, Sch Elect & Elect Engn, Wuhan 430068, Peoples R China
关键词
Parameter estimation; Gradient search; Least squares; Multi-innovation identification; Stochastic system; IDENTIFICATION; DELAY;
D O I
10.1016/j.sysconle.2025.106166
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers the parameter estimation problems of general linear time-invariant continuous-time systems described by higher-order constant coefficient differentiate equations. This paper derives the two-stage parameter estimation model of the systems, which contains two parameter vectors, one corresponds to the coefficients of the denominator polynomial of the transfer function and the other corresponds to the coefficients of the numerator polynomial of the transfer function. Furthermore, we propose two-stage projection estimation algorithm, two-stage generalized projection estimation algorithm, two-stage stochastic gradient estimation algorithm, two-stage recursive least squares estimation algorithm and their variants. The proposed algorithms can be extended to investigate the parameter estimation of other linear stochastic systems with colored noises.
引用
收藏
页数:14
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