Artificial Neural Networks and Fuzzy Logic in Process Modeling and Control

被引：0

作者：

Reel, Smarti ^{[1
]}

Goel, Ashok Kumar ^{[1
]}

机构：

[1] Thapar Univ, Elect & Commun Engn Dept, Patiala 147001, Punjab, India

来源：

COMPUTATIONAL INTELLIGENCE AND INFORMATION TECHNOLOGY | 2011年 / 250卷

关键词：

Artificial-Neural-Networks; Fuzzy-Logic; Neuro-Fuzzy-Systems;

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 presents a review on application of Artificial Neural Network and Fuzzy Logic in process modeling and control. The intelligent control techniques are rapidly replacing the conventional control due to their abilities like learning, function approximation, associative memory, prediction, combinatorial optimization and non-linear system modeling etc. In this paper, research work done in process modeling and control using conventional techniques, Artificial Neural Networks, Fuzzy Logic and Neuro-Fuzzy paradigms is discussed. For each control methodology its corresponding limitations are also presented. An outline of recent alternative approaches for process modeling and control are also included.

引用

页码：808 / 810

页数：3

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