TY - GEN
T1 - A fuzzy adaptive set-point regulator design
AU - Yesil, E.
AU - Guzelkaya, M.
AU - Eksin, I.
PY - 2012
Y1 - 2012
N2 - In this paper, an online tuned set-point regulator with a fuzzy mechanism is proposed. This proposed control structure exploits the advantages of one degree of freedom (1-DOF) and two degree of freedom (2-DOF) control forms. The blending mechanism of the set point regulator mix the filtered and pure reference signals so that the overall performance of the system is ameliorated with respect to load disturbance rejection and set-point following. In the proposed control structure, the PI controller is designed by using Internal Model Control (IMC) methodology. As a result of this chose, the proposed blending mechanism turns out to be a blending constant within the range of zero and one. Consequently, this blending constant can easily be tuned through a fuzzy inference mechanism, where the output signal is naturally the blending constant. First, the effectiveness of the proposed fuzzy adaptive set-point regulator is demonstrated and compared via simulations and then an experimental setup is design to show the applicability of the proposed control approach. The simulation and the experimental results show the benefit of the proposed method over the conventional counterparts.
AB - In this paper, an online tuned set-point regulator with a fuzzy mechanism is proposed. This proposed control structure exploits the advantages of one degree of freedom (1-DOF) and two degree of freedom (2-DOF) control forms. The blending mechanism of the set point regulator mix the filtered and pure reference signals so that the overall performance of the system is ameliorated with respect to load disturbance rejection and set-point following. In the proposed control structure, the PI controller is designed by using Internal Model Control (IMC) methodology. As a result of this chose, the proposed blending mechanism turns out to be a blending constant within the range of zero and one. Consequently, this blending constant can easily be tuned through a fuzzy inference mechanism, where the output signal is naturally the blending constant. First, the effectiveness of the proposed fuzzy adaptive set-point regulator is demonstrated and compared via simulations and then an experimental setup is design to show the applicability of the proposed control approach. The simulation and the experimental results show the benefit of the proposed method over the conventional counterparts.
UR - http://www.scopus.com/inward/record.url?scp=84876919566&partnerID=8YFLogxK
U2 - 10.1109/CINTI.2012.6496781
DO - 10.1109/CINTI.2012.6496781
M3 - Conference contribution
AN - SCOPUS:84876919566
SN - 9781467352062
T3 - CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings
SP - 311
EP - 316
BT - CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings
T2 - 13th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2012
Y2 - 20 November 2012 through 22 November 2012
ER -