Adaptive control for a class of nonlinear time-varying systems

Author

Diao, Yixin ; Passino, Kevin M.

Author_Institution

IBM Thomas J. Watson Res. Center, Hawthorne, NY, USA

Volume

6

fYear

2001

fDate

2001

Firstpage

4161

Abstract

Adaptive control for nonlinear time-varying systems is of both theoretical and practical importance. We present an adaptive control methodology for a class of nonlinear systems with a time-varying structure where radial basis function neural networks are used as on-line approximators. This class of systems is composed of interpolations of nonlinear subsystems which are input-output feedback linearizable. Without assumptions on rate of change of system dynamics, a stable indirect adaptive control method is presented with analysis of stability for all signals in the closed-loop as well as asymptotic tracking. The performance of the controller is demonstrated using a jet engine control problem

Keywords

adaptive control; aerospace control; aerospace engines; feedback; neurocontrollers; nonlinear control systems; radial basis function networks; time-varying systems; asymptotic tracking; input-output feedback linearizable systems; interpolations; jet engine control problem; nonlinear time-varying systems; online approximators; radial basis function neural networks; stable indirect adaptive control method; Adaptive control; Asymptotic stability; Interpolation; Neurofeedback; Nonlinear dynamical systems; Nonlinear systems; Radial basis function networks; Signal analysis; Stability analysis; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2001. Proceedings of the 2001

Conference_Location

Arlington, VA

ISSN

0743-1619

Print_ISBN

0-7803-6495-3

Type

conf

DOI

10.1109/ACC.2001.945628

Filename

945628