State Estimation for a Class of Nonlinear Differential Games using Differential Neural Networks

被引：0

作者：

Garcia, Emmanuel ^{[1
]}

Murano, Daishi A. ^{[1
]}

机构：

[1] ITESM CEM, Dept Mech & Mechatron, Atizapan De Zaragoza 52926, State Of Mexico, Mexico

来源：

2011 AMERICAN CONTROL CONFERENCE | 2011年

关键词：

Differential games; dynamic neural networks; state observers;

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：

This paper deals with the problem of the state estimation for a certain class of nonlinear differential games, where the mathematical model of this class is completely unknown. Being thus, a Luenberger-like differential neural network observer is applied and a new learning law for its synaptic weights is suggested. Furthermore, by means of a Lyapunov stability analysis, the stability conditions for the state estimation error are established and the upper bound of this error is obtained. Finally, a numerical example illustrates the applicability of this approach.

引用

下载

页码：2486 / 2491

页数：6

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