TY - GEN
T1 - Online fuzzy rule weighting method for fuzzy PID controllers via Big Bang-Big Crunch optimization
AU - Yesil, Engin
AU - Sakalli, Ahmet
AU - Ozturk, Cihan
AU - Kumbasar, Tufan
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Big Bang - Big Crunch optimization
KW - Fuzzy PID controller
KW - Fuzzy rule weighting
KW - Heating process
KW - Self-tuning control
UR - http://www.scopus.com/inward/record.url?scp=84887843182&partnerID=8YFLogxK
U2 - 10.1109/FUZZ-IEEE.2013.6622405
DO - 10.1109/FUZZ-IEEE.2013.6622405
M3 - Conference contribution
AN - SCOPUS:84887843182
SN - 9781479900220
T3 - IEEE International Conference on Fuzzy Systems
BT - FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems
T2 - 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013
Y2 - 7 July 2013 through 10 July 2013
ER -