Abstract
In this paper, a single and multi-layer neural network (NN) controllers are developed for a class of nonlinear discrete time systems. under a mild assumption on the system uncertainties, which include unmodeled dynamics and bounded disturbances, by using novel weight update laws and a robust term, local asymptotic stability of the closed-loop system is guaranteed in contrast with all other NN controllers where a uniform ultimate boundedness is normally shown. Simulation results are presented to show the effectiveness of the controller design. © 2009 AACC.
Recommended Citation
B. T. Thumati and S. Jagannathan, "Neural Network Control of a Class of Nonlinear Discrete Time Systems with Asymptotic Stability Guarantees," Proceedings of the American Control Conference, pp. 2934 - 2939, article no. 5160469, Institute of Electrical and Electronics Engineers, Nov 2009.
The definitive version is available at https://doi.org/10.1109/ACC.2009.5160469
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
International Standard Book Number (ISBN)
978-142444524-0
International Standard Serial Number (ISSN)
0743-1619
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
23 Nov 2009
