TY - JOUR
T1 - Online tuning of fuzzy PID controllers via rule weighing based on normalized acceleration
AU - Karasakal, Onur
AU - Guzelkaya, Mujde
AU - Eksin, Ibrahim
AU - Yesil, Engin
AU - Kumbasar, Tufan
PY - 2013/1
Y1 - 2013/1
N2 - In this study, an on-line tuning method is proposed for fuzzy PID controllers via rule weighing. The rule weighing mechanism is a fuzzy rule base with two inputs namely; error and normalized acceleration. Here, the normalized acceleration provides relative information on the fastness or slowness of the system response. In deriving the fuzzy rules of the weighing mechanism, the transient phase of the unit step response of the closed loop system is to be analyzed. For this purpose, this response is assumed to be divided into certain regions, depending on the number of membership functions defined for the error input of the fuzzy logic controller. Then, the relative importance or influence of the fired fuzzy rules is determined for each region of the transient phase of the unit step response of the closed loop system. The output of the fuzzy rule weighing mechanism is charged as the tuning variable of the rule weights; and, in this manner, an on-line self-tuning rule weight assignment is accomplished. The effectiveness of the proposed on-line weight adjustment method is demonstrated on linear and non-linear systems by simulations. Moreover, a real time application of this new method is accomplished on a pH neutralization process.
AB - In this study, an on-line tuning method is proposed for fuzzy PID controllers via rule weighing. The rule weighing mechanism is a fuzzy rule base with two inputs namely; error and normalized acceleration. Here, the normalized acceleration provides relative information on the fastness or slowness of the system response. In deriving the fuzzy rules of the weighing mechanism, the transient phase of the unit step response of the closed loop system is to be analyzed. For this purpose, this response is assumed to be divided into certain regions, depending on the number of membership functions defined for the error input of the fuzzy logic controller. Then, the relative importance or influence of the fired fuzzy rules is determined for each region of the transient phase of the unit step response of the closed loop system. The output of the fuzzy rule weighing mechanism is charged as the tuning variable of the rule weights; and, in this manner, an on-line self-tuning rule weight assignment is accomplished. The effectiveness of the proposed on-line weight adjustment method is demonstrated on linear and non-linear systems by simulations. Moreover, a real time application of this new method is accomplished on a pH neutralization process.
KW - Fuzzy PID controller
KW - Fuzzy rule weighting
KW - Normalized acceleration
KW - Self-tuning control
KW - pH neutralization process
UR - http://www.scopus.com/inward/record.url?scp=84870066338&partnerID=8YFLogxK
U2 - 10.1016/j.engappai.2012.06.005
DO - 10.1016/j.engappai.2012.06.005
M3 - Article
AN - SCOPUS:84870066338
SN - 0952-1976
VL - 26
SP - 184
EP - 197
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
IS - 1
ER -