Neural network control of a class of nonlinear discrete time systems with asymptotic stability guarantees

Authors:
Balaje T. Thumati;S. Jagannathan
Affiliations:
Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO;Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 4
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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.