Online fuzzy rule weighting method for fuzzy PID controllers via Big Bang-Big Crunch optimization

Engin Yesil, Ahmet Sakalli, Cihan Ozturk, Tufan Kumbasar

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

3 Citations (Scopus)

Abstract

In this study, a novel online tuning method is proposed for fuzzy PID controllers via rule weighting. The rule weighting is performed with a fast evolutionary algorithm called Big Bang - Big Crunch (BB-BC) optimization algorithm which has a low computational time. In this study, the rule weights are selected as tuning parameter of fuzzy PID controller instead of structural parameter in order to improve the transient and steady state performance of the process. The BB-BC algorithm calculates the optimal rule weights that force the process output to follow the reference signal with an applicable control signal at each sampling period. The effectiveness of the proposed online rule weighting method is demonstrated on heat transfer process (PT-326 Process Trainer) in real time with comparisons. The results illustrate that the proposed online rule weighting method significantly improves the performance of the fuzzy PID controller structure.

Original languageEnglish
Title of host publicationFUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems
DOIs
Publication statusPublished - 2013
Event2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad, India
Duration: 7 Jul 201310 Jul 2013

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013
Country/TerritoryIndia
CityHyderabad
Period7/07/1310/07/13

Keywords

  • Big Bang - Big Crunch optimization
  • Fuzzy PID controller
  • Fuzzy rule weighting
  • Heating process
  • Self-tuning control

Fingerprint

Dive into the research topics of 'Online fuzzy rule weighting method for fuzzy PID controllers via Big Bang-Big Crunch optimization'. Together they form a unique fingerprint.

Cite this