期刊
ISA TRANSACTIONS
卷 59, 期 -, 页码 363-374出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2015.09.003
关键词
Lyapunov function Neural tracking; Decentralized control; Direct adaptive inverse control; Indirect adaptive Inverse control; Stable adaptive tracking
资金
- Sultan Qaboos University, Oman
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.
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