Neural network adaptive control with fuzzy rules confirming initial weights

Guiyong Ren; Yancheng Qu; Changhong Wang

Neural network adaptive control with fuzzy rules confirming initial weights

Guiyong Ren
, Yancheng Qu
, Changhong Wang

School of Astronautics

Research output: Contribution to conference › Paper › peer-review

Abstract

A new method, based on fuzzy rules, is presented to learn the initial values of neural network's weight array. This neural network is used in adaptive control architecture. Using the prior knowledge efficiently, it can ensure the stability of the adaptive control during the learning period of the neural network. The simulation results demonstrate the feasibility of this method.

Original language	English
Pages	931-934
Number of pages	4
State	Published - 2000
Event	Proceedings of the 3th World Congress on Intelligent Control and Automation - Hefei, China Duration: 28 Jun 2000 → 2 Jul 2000

Conference

Conference	Proceedings of the 3th World Congress on Intelligent Control and Automation
Country/Territory	China
City	Hefei
Period	28/06/00 → 2/07/00

Keywords

Fuzzy Control
Neural Network Control
Prior Knowledge

Cite this

@conference{98373081deb74fed8b9028a95a7e34de,

title = "Neural network adaptive control with fuzzy rules confirming initial weights",

abstract = "A new method, based on fuzzy rules, is presented to learn the initial values of neural network's weight array. This neural network is used in adaptive control architecture. Using the prior knowledge efficiently, it can ensure the stability of the adaptive control during the learning period of the neural network. The simulation results demonstrate the feasibility of this method.",

keywords = "Fuzzy Control, Neural Network Control, Prior Knowledge",

author = "Guiyong Ren and Yancheng Qu and Changhong Wang",

year = "2000",

language = "英语",

pages = "931--934",

note = "Proceedings of the 3th World Congress on Intelligent Control and Automation ; Conference date: 28-06-2000 Through 02-07-2000",

}

TY - CONF

T1 - Neural network adaptive control with fuzzy rules confirming initial weights

AU - Ren, Guiyong

AU - Qu, Yancheng

AU - Wang, Changhong

PY - 2000

Y1 - 2000

N2 - A new method, based on fuzzy rules, is presented to learn the initial values of neural network's weight array. This neural network is used in adaptive control architecture. Using the prior knowledge efficiently, it can ensure the stability of the adaptive control during the learning period of the neural network. The simulation results demonstrate the feasibility of this method.

AB - A new method, based on fuzzy rules, is presented to learn the initial values of neural network's weight array. This neural network is used in adaptive control architecture. Using the prior knowledge efficiently, it can ensure the stability of the adaptive control during the learning period of the neural network. The simulation results demonstrate the feasibility of this method.

KW - Fuzzy Control

KW - Neural Network Control

KW - Prior Knowledge

UR - https://www.scopus.com/pages/publications/0034591685

M3 - 论文

AN - SCOPUS:0034591685

SP - 931

EP - 934

T2 - Proceedings of the 3th World Congress on Intelligent Control and Automation

Y2 - 28 June 2000 through 2 July 2000

ER -

Neural network adaptive control with fuzzy rules confirming initial weights

Abstract

Conference

Keywords

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Cite this