Neural networks for tracking of unknown SISO discrete-time nonlinear dynamic systems

被引：12

作者：

Aftab, Muhammad Saleheen ^{[1
]}

Shafiq, Muhammad ^{[1
]}

机构：

[1] Sultan Qaboos Univ, Dept Elect & Comp Engn, Muscat, Oman

来源：

ISA TRANSACTIONS | 2015年 / 59卷

关键词：

Lyapunov function Neural tracking; Decentralized control; Direct adaptive inverse control; Indirect adaptive Inverse control; Stable adaptive tracking; ADAPTIVE-CONTROL; BACKPROPAGATION;

D O I：

10.1016/j.isatra.2015.09.003

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 article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator parameters. The controller and estimator error convergence and closed-loop system stability analysis is performed by Lyapunov stability theory. Moreover, two simulation examples and one real-time experiment are investigated as case studies. The achieved results successfully validate the controller performance. (C) 2015 ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：363 / 374

页数：12

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