REGULATION OF UNKNOWN NONLINEAR DYNAMICAL-SYSTEMS VIA DYNAMICAL NEURAL NETWORKS

被引：3

作者：

ROVITHAKIS, GA

CHRISTODOULOU, MA

机构：

[1] Department of Electronic and Computer Engineering, Technical University of Crete, Chania, Crete

来源：

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 1995年 / 12卷 / 03期

关键词：

ADAPTIVE REGULATION; NONLINEAR SYSTEMS; DYNAMICAL NEURAL NETWORKS;

D O I：

10.1007/BF01262964

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we are dealing with the problem of regulating unknown nonlinear dynamical systems. First a dynamical neural network identifier is employed to perform 'black box' identification and then a regular static feedback is developed to regulate the unknown system to zero. Not all the plant states are assumed to be available for measurement.

引用

页码：259 / 275

页数：17

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