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Title: Variable Neural Adaptive Robust Control: A Switched System Approach

Abstract

Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

Authors:
; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1182900
Report Number(s):
PNNL-SA-90777
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Neural Networks and Learning Systems, 26(5):903-915
Additional Journal Information:
Journal Name: IEEE Transactions on Neural Networks and Learning Systems, 26(5):903-915
Country of Publication:
United States
Language:
English
Subject:
neural; adaptive; IEEE; Tansactions; learning systems

Citation Formats

Lian, Jianming, Hu, Jianghai, and Zak, Stanislaw H. Variable Neural Adaptive Robust Control: A Switched System Approach. United States: N. p., 2015. Web. doi:10.1109/TNNLS.2014.2327853.
Lian, Jianming, Hu, Jianghai, & Zak, Stanislaw H. Variable Neural Adaptive Robust Control: A Switched System Approach. United States. doi:10.1109/TNNLS.2014.2327853.
Lian, Jianming, Hu, Jianghai, and Zak, Stanislaw H. Fri . "Variable Neural Adaptive Robust Control: A Switched System Approach". United States. doi:10.1109/TNNLS.2014.2327853.
@article{osti_1182900,
title = {Variable Neural Adaptive Robust Control: A Switched System Approach},
author = {Lian, Jianming and Hu, Jianghai and Zak, Stanislaw H.},
abstractNote = {Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.},
doi = {10.1109/TNNLS.2014.2327853},
journal = {IEEE Transactions on Neural Networks and Learning Systems, 26(5):903-915},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {5}
}