Adaptive recurrent neural control for noisy chaos synchronization

被引：0
|
作者：
Sanchez, EN [1 ]
Perez, JP [1 ]
机构：
[1] CINVESTAV, Unidad Guadalajara, Guadalajara 45091, Jalisco, Mexico
来源：
PROCEEDINGS OF THE 2003 AMERICAN CONTROL CONFERENCE, VOLS 1-6 | 2003年
关键词：
recurrent neural networks; stochastic systems; trajectory tracking; chaos synchronization; Lyapunov methodology;
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：
In this paper, we present an adaptive recurrent neural control for trajectory tracking of noisy unknown nonlinear systems. Trajectory tracking error stability is analyzed by means of the stochastic system extension for the Lyapunov methodology. The applicability of the proposed structure is illustrated, via simulations, with a relevant complex task: noisy chaos synchronization.
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页码：1290 / 1295
页数：6
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