Neural regulator design

被引：6

作者：

Ahmed, MS ^{[1
]}

Al-Dajani, MA

机构：

[1] King Fahd Univ Petr & Minerals, Dept Syst Engn, Dhahran 31261, Saudi Arabia

[2] Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90024 USA

来源：

NEURAL NETWORKS | 1998年 / 11卷 / 09期

关键词：

neural network; control system; regulation; nonlinear systems; optimization; gradient scheme;

D O I：

10.1016/S0893-6080(98)00097-5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Design of a neural-net-based regulator for nonlinear plants is considered. Both state and output feedback regulators with deterministic and stochastic disturbances have been investigated. A Multilayered Feedforward Neural Network (MFNN) has been employed as the nonlinear controller. The training of the MFNN utilizes the recently developed concept of Block Partial Derivatives (BPDs). (C) 1998 Elsevier Science Ltd. All rights reserved.

引用

页码：1695 / 1709

页数：15

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