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

被引：0
作者：
Dan Yang
Yanjun Liu
Feng Ding
Erfu Yang
机构：
[1] Jiangnan University,Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering
[2] Changzhou Vocational Institute of Textile and Garment,Department of Electromechanical Engineering
[3] University of Strathclyde,Department of Design, Manufacturing and Engineering Management
来源：
Circuits, Systems, and Signal Processing | 2024年 / 43卷
关键词：
Nonlinear feedback system; Iterative identification; Hierarchical identification; Gradient search; Parameter estimation;
D O I：
暂无
中图分类号：
学科分类号：
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：27
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