A Newton-type Iterative Learning Algorithm of Output Tracking Control for Uncertain Nonlinear Distributed Parameter Systems

被引：0
|
作者：
Kang Jingli [1 ]
机构：
[1] China Aerosp Sci & Technol Corp, Acad 4, Beijing 102308, Peoples R China
来源：
2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年
关键词：
Iterative learning control; Nonlinear distributed parameter systems; Newton method; Parabolic partial differential equations;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new iterative learning algorithm of output tracking control for uncertain nonlinear distributed parameter systems is considered in this paper. The iterative learning control scheme based on Newton-type method is constructed. Sufficient conditions for the convergence of this new algorithm are given. Using Green formula and the operator Taylor expansion method in Banach space, the convergence of the Newton-type iterative learning control algorithm is proved. The significant of this paper is to provide a Newton-type iterative learning control scheme with rapid convergence speed, which is a new method for solving the output tracking problem in distributed parameter systems.
引用
收藏
页码：8895 / 8899
页数：5
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