Inverse fuzzy model control with online adaptation via big bang-big crunch optimization

Tufan Kumbasar*, Engin Yeşil, Ibrahim Eksin, Müjde Güzelkaya

*Corresponding author for this work

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

37 Citations (Scopus)

Abstract

Fuzzy logic modeling is a powerful tool in representing nonlinear systems. Moreover, inverse fuzzy model can be used as a controller in an open loop fashion to produce perfect control. However, in the case of modeling mismatches and disturbances that might occur on the system, open loop control would not be sufficient. In that case, the modeling errors and disturbances could be compensated by Internal Model Control (IMC) with an on-line model adaptation scheme. The on-line adaptation is usually accomplished via recursive least square algorithm. In this study, Big Bang-Big Crunch (BB-BC) optimization method, which has a low computational time and high convergence speed, has been used as an on-line adaptation scheme. The inverse fuzzy model based IMC and the BB-BC optimization method based adaptation have been implemented and tested on a real time heating process system.

Original languageEnglish
Title of host publication2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008
Pages697-702
Number of pages6
DOIs
Publication statusPublished - 2008
Event2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008 - St. Julians, Malta
Duration: 12 Mar 200814 Mar 2008

Publication series

Name2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP 2008

Conference

Conference2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008
Country/TerritoryMalta
CitySt. Julians
Period12/03/0814/03/08

Keywords

  • Big bang- Big crunch optimization
  • Fuzzy logic
  • Fuzzy model inversion
  • Heating process

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