Hierarchical Gradient-Based Iterative Parameter Estimation Algorithms for a Nonlinear Feedback System Based on the Hierarchical Identification Principle

被引：53
作者：
Yang, Dan [1 ,2 ]
Liu, Yanjun [1 ]
Ding, Feng [1 ]
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] Changzhou Vocat Inst Text & Garment, Dept Electromech Engn, Changzhou 213164, Peoples R China
[3] Univ Strathclyde, Dept Design Mfg & Engn Management, Glasgow G1 1XJ, Scotland
来源：
CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2024年 / 43卷 / 01期
基金：
上海市自然科学基金; 中国国家自然科学基金;
关键词：
Nonlinear feedback system; Iterative identification; Hierarchical identification; Gradient search; Parameter estimation; SUBSPACE IDENTIFICATION; MULTI-INNOVATION; FAULT-DIAGNOSIS; DELAY; OPTIMIZATION; TRACKING;
D O I：
10.1007/s00034-023-02477-1
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper focuses on iterative parameter estimation methods for a nonlinear closed-loop system (i.e., a nonlinear feedback system) with an equation-error model for the open-loop part. By applying negative gradient search, a gradient-based iterative algorithm is constructed. To reduce the computational costs and improve the parameter estimation accuracy, the hierarchical identification principle is employed to derive a hierarchical gradient-based iterative algorithm. A simulation example is provided to test the effectiveness of the proposed algorithms.
引用
收藏
页码：124 / 151
页数：28
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