Artificial Neural Networks and Fuzzy Logic in Process Modeling and Control

Smarti Reel, Ashok Kumar Goel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationComputational Intelligence and Information Technology
Subtitle of host publicationFirst International Conference, CIIT 2011, Pune, India, November 2011 Proceedings
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages808-810
Number of pages3
ISBN (Electronic)9783642257346
ISBN (Print)9783642257339
DOIs
Publication statusPublished - Nov 2011
EventInternational Conference on Computational Intelligence and Information Technology, CIIT 2011 - Pune, India
Duration: 7 Nov 20118 Nov 2011
http://ciit.theides.org/2011/ (Link to conference information)

Publication series

NameCommunications in Computer and Information Science (CCIS)
Volume250
ISSN (Print)1865-0929

Conference

ConferenceInternational Conference on Computational Intelligence and Information Technology, CIIT 2011
Abbreviated titleCIIT 2011
Country/TerritoryIndia
CityPune
Period7/11/118/11/11
Internet address

Keywords

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

ASJC Scopus subject areas

  • General Computer Science

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