Implementations of a Hammerstein fuzzy-neural model for predictive control of a lyophilization plant

Yancho Todorov, Sevil Ahmed, Michail Petrov, Vasilliy Chitanov

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

5 Citations (Scopus)

Abstract

This paper describes two methodologies for implementation of Hammerstein model by using different input-output representations into model predictive control schemes. The model nonlinearity is easily approximated using a simple Takagi-Sugeno inference, while the linear parts are flexibly introduced. As optimization procedures for predictive control are used a standard gradient optimization method and an implementation of Hildreth Quadratic Programming. A comparison between the proposed control strategies is made by simulation experiments for control of nonlinear lyophilization plant.

Original languageEnglish
Title of host publication2012 6th IEEE International Conference Intelligent Systems
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages316-321
ISBN (Electronic)978-1-4673-2278-2, 978-1-4673-2277-5
ISBN (Print)978-1-4673-2276-8
DOIs
Publication statusPublished - 28 Nov 2012
MoE publication typeA4 Article in a conference publication
Event2012 6th IEEE International Conference Intelligent Systems, IS 2012 - Sofia, Bulgaria
Duration: 6 Sep 20128 Sep 2012

Conference

Conference2012 6th IEEE International Conference Intelligent Systems, IS 2012
CountryBulgaria
CitySofia
Period6/09/128/09/12

Keywords

  • fuzzy-neural models
  • gradient descent
  • Hildreth quadratic programming
  • lyophilization
  • optimization
  • predictive control

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    Todorov, Y., Ahmed, S., Petrov, M., & Chitanov, V. (2012). Implementations of a Hammerstein fuzzy-neural model for predictive control of a lyophilization plant. In 2012 6th IEEE International Conference Intelligent Systems (pp. 316-321). [6335154] IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/IS.2012.6335154