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Intelligent Neuro-fuzzy Based Predictive Control of a Continuous Stirred Tank Reactor

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

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Abstract

In this paper, a predictive control strategy based on neuro-fuzzy (NF) model of the plant is applied to Continuous Stirred Tank Reactor (CSTR). An optimizer algorithm based on evolutionary programming technique (EP) uses the identifier-predicted outputs and determines input sequence in a time window. Using the proposed neuro-fuzzy predictive controller, the performance of Ph tracking problem in a CSTR process is investigated.

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Author information

Authors and Affiliations

  1. Young Researchers Club, Islamic Aazd University, Tehran, Iran

    Mahdi Jalili-Kharaajoo & Farzad Habibipour Roudsari

Authors
  1. Mahdi Jalili-Kharaajoo
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  2. Farzad Habibipour Roudsari
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Jalili-Kharaajoo, M., Habibipour Roudsari, F. (2005). Intelligent Neuro-fuzzy Based Predictive Control of a Continuous Stirred Tank Reactor. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_105

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  • DOI: https://doi.org/10.1007/11427469_105

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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