Newton-method based iterative learning control for sampled nonlinear systems

Author

Lin, T. ; Owens, H. ; Hätönen, J.

Author_Institution

Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK

fYear

2005

fDate

10-13 July 2005

Firstpage

142

Lastpage

147

Abstract

Iterative learning control (ILC) has been an intensely researched area. Significant progress has been achieved in terms of both theory and applications of ILC to industrial problems. This paper focuses on applying ILC to sampled nonlinear systems in continuous time domain. The main result of this paper is a new nonlinear ILC algorithm that utilizes a special form of the Newton method. This special form allows one to decompose the original nonlinear ILC problem into a sequence of linear time-varying ILC problems. Conditions for the semi-local convergence of the new ILC algorithm are also established.

Keywords

Newton method; continuous time systems; convergence; learning (artificial intelligence); nonlinear control systems; position control; Newton-method based iterative learning control; continuous time domain; nonlinear systems; semilocal convergence; Automatic control; Control systems; Convergence; Electrical equipment industry; Error correction; Iterative algorithms; Newton method; Nonlinear control systems; Nonlinear systems; Optimal control;

fLanguage

English

Publisher

ieee

Conference_Titel

Multidimensional Systems, 2005. NDS 2005. The Fourth International Workshop on

Print_ISBN

3-9810299-8-4

Type

conf

DOI

10.1109/NDS.2005.195344

Filename

1507846