Robust backstepping control of nonlinear systems in discrete-time using multilayer neural networks

Author

Jagannathan, S.

Author_Institution

Automated Analysis Corp., Peoria, IL., USA

Volume

1

fYear

1997

fDate

10-12 Dec 1997

Firstpage

480

Abstract

A multilayer neural network (NN) controller for the robust backstepping control of nonlinear systems in discrete-time is presented. Control action is employed to achieve tracking performance for unknown nonlinear systems. Tuning methods are derived for the multilayer NN based on the delta rule. Uniform ultimate boundedness of the tracking error and the weight estimates are presented without using the PE condition. No learning phase is needed for the NN and initialization of the network weights is straightforward

Keywords

discrete time systems; multilayer perceptrons; neurocontrollers; nonlinear control systems; robust control; tracking; tuning; uncertain systems; control action; multilayer neural networks; nonlinear systems; robust backstepping control; tracking error; tracking performance; tuning methods; uniform ultimate boundedness; weight estimates; Adaptive control; Automatic control; Backstepping; Control systems; Intelligent networks; Multi-layer neural network; Neural networks; Nonlinear control systems; Nonlinear systems; Robust control;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on

Conference_Location

San Diego, CA

ISSN

0191-2216

Print_ISBN

0-7803-4187-2

Type

conf

DOI

10.1109/CDC.1997.650672

Filename

650672