A Locally Weighted Learning Method for Nonaffine-in-Control Systems

Author

Zhao, Y. ; Farrell, J.A.

Author_Institution

Dept. of Electr. Eng., California Univ., Riverside, CA

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

3454

Lastpage

3460

Abstract

This article is concerned with tracking control problems for nonlinear systems that are not affine in the control signal and that contain unknown nonlinearities in the system dynamic equations. This paper develops a piecewise linear approximation to the unknown functions during system operation. New control and parameter adaptation algorithms are designed and analyzed using Lyapunov-like methods. The objectives are to achieve global stability of the state, accurate tracking of bounded reference signals contained within a known domain D_x, and at least boundedness of the function approximation parameter estimates

Keywords

Lyapunov methods; adaptive control; control nonlinearities; control system synthesis; function approximation; learning systems; nonlinear control systems; parameter estimation; stability; tracking; Lyapunov-like methods; adaptive nonlinear control; function approximation; global stability; nonaffine-in-control systems; nonlinear systems; parameter adaptation algorithms; parameter estimation; piecewise linear approximation; system dynamic equation; tracking control; unknown nonlinearities; weighted learning; Algorithm design and analysis; Control nonlinearities; Control systems; Learning systems; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Piecewise linear approximation; Stability; Adaptive approximation based control; adaptive nonlinear control; locally weighted learning; nonaffine-in-control systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2006 45th IEEE Conference on

Conference_Location

San Diego, CA

Print_ISBN

1-4244-0171-2

Type

conf

DOI

10.1109/CDC.2006.377279

Filename

4177110