Nonlinear iterative learning by an adaptive Lyapunov technique

Author

French, M. ; Rogers, E.

Author_Institution

Dept. of Electron. & Comput. Sci., Southampton Univ., UK

Volume

1

fYear

1998

fDate

1998

Firstpage

175

Abstract

We consider parametrically uncertain systems satisfying a matching condition. A standard Lyapunov adaptive design for stabilization is modified to ensure a monotonically decreasing parametric error. This modified controller is used to learn a control which forces the state to reach a neighbourhood of the origin at a time t>0 in a finite number of learning passes of finite length. A performance analysis is completed. The iterative learning tracking problem is also considered. Corresponding results can also be obtained for strict feedback systems via adaptive backstepping, and this is briefly sketched

Keywords

Lyapunov methods; adaptive control; control system synthesis; feedback; iterative methods; nonlinear control systems; stability; tracking; uncertain systems; Lyapunov method; adaptive control; backstepping; feedback; iterative learning control; nonlinear control systems; stabilization; tracking; uncertain systems; Adaptive control; Backstepping; Computer errors; Computer science; Error correction; Feedback; Force control; Performance analysis; Uncertain systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1998. Proceedings of the 37th IEEE Conference on

Conference_Location

Tampa, FL

ISSN

0191-2216

Print_ISBN

0-7803-4394-8

Type

conf

DOI

10.1109/CDC.1998.760617

Filename

760617