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. https://doi.org/10.1109/TNNLS.2014.2327853
Lian, Jianming, Hu, Jianghai, and Zak, Stanislaw H. 2015.
"Variable Neural Adaptive Robust Control: A Switched System Approach". United States. https://doi.org/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},
url = {https://www.osti.gov/biblio/1182900},
journal = {IEEE Transactions on Neural Networks and Learning Systems, 26(5):903-915},
number = ,
volume = ,
place = {United States},
year = {Fri May 01 00:00:00 EDT 2015},
month = {Fri May 01 00:00:00 EDT 2015}
}