@inproceedings{dcf573f224114bf39b4b22cfd63c6c48,
title = "Online fuzzy rule weighting method for fuzzy PID controllers via Big Bang-Big Crunch optimization",
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.",
keywords = "Big Bang - Big Crunch optimization, Fuzzy PID controller, Fuzzy rule weighting, Heating process, Self-tuning control",
author = "Engin Yesil and Ahmet Sakalli and Cihan Ozturk and Tufan Kumbasar",
year = "2013",
doi = "10.1109/FUZZ-IEEE.2013.6622405",
language = "English",
isbn = "9781479900220",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems",
address = "United States",
note = "2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 ; Conference date: 07-07-2013 Through 10-07-2013",
}