Title :
A new iterative learning control algorithm with global convergence for nonlinear systems
Author_Institution :
Dept. of Math., Tianjin Univ. of Finance & Econ., Tianjin, China
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;
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
DOI :
10.1109/ICCASM.2010.5623164
