An Adaptive Neural Identifier with Applications to Financial and Welding Systems

被引：5

作者：

Guiarte, Kevin Herman Muraro ^{[1
]}

Chavez, Jairo Jose Munoz ^{[2
]}

Vargas, Jose Alfredo Ruiz ^{[1
]}

Alfaro, Sadek Crisostomo Absi ^{[2
]}

机构：

[1] Univ Brasilia, Dept Engn Eletr, BR-70910900 Brasilia, DF, Brazil

[2] Univ Brasilia, Dept Engn Mecan, BR-70910900 Brasilia, DF, Brazil

来源：

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2021年 / 19卷 / 05期

关键词：

Lyapunov theory; neural networks; online identification; weld geometry prediction; NONLINEAR DYNAMICAL-SYSTEMS; PREDICTION; NETWORKS; OPTIMIZATION; GEOMETRY; ALGORITHM; ELM;

D O I：

10.1007/s12555-020-0081-x

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 online identification problem of uncertain systems. Based on parallel and series-parallel configurations with feedback and by using Lyapunov arguments, a unified identification algorithm is introduced to ensure the boundedness of all associated errors and convergence of the state estimation error to an arbitrary neighborhood of the origin. The main peculiarity of the proposed algorithm lies in allowing the adjustment of the identification transient by using parameters that are not related to the residual state error. Two examples are deemed to validate the theoretical results and show the relevance of the application of the proposed methodology for online weld geometry prediction.

引用

页码：1976 / 1987

页数：12

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