DocumentCode
533190
Title
A new iterative learning control algorithm with global convergence for nonlinear systems
Author
Kang, Jingli
Author_Institution
Dept. of Math., Tianjin Univ. of Finance & Econ., Tianjin, China
Volume
11
fYear
2010
fDate
22-24 Oct. 2010
Abstract
In this paper, a new iterative learning control algorithm with global convergence for nonlinear systems is presented. By introduced a relax parameter, the global convergence of this new algorithm is obtained. The new iterative learning scheme can be used to nonlinear systems where dimensions of input controls are not equal to dimensions of the output function. The sufficient conditions of convergence of the iterative learning control algorithm are given and proved.
Keywords
iterative methods; learning systems; nonlinear control systems; global convergence; iterative learning control; nonlinear system; Control systems; Convergence; Iterative algorithm; Iterative methods; Modeling; Nonlinear systems; Sufficient conditions; Gauss-Newton method; Iterative learning control; global convergence; nonlinear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Electronic_ISBN
978-1-4244-7237-6
Type
conf
DOI
10.1109/ICCASM.2010.5623164
Filename
5623164
Link To Document