• DocumentCode
    226609
  • Title

    Performance evaluation of interval type-2 and online rule weighing based Type-1 Fuzzy PID controllers on a pH process

  • Author

    Kumbasar, Tufan ; Ozturk, Cengizhan ; Yesil, Engin ; Hagras, Hani

  • Author_Institution
    Control & Autom. Eng. Dept., Istanbul Tech. Univ., Istanbul, Turkey
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1875
  • Lastpage
    1882
  • Abstract
    In this paper, we will explore whether the efficiency of the Interval Type-2 Fuzzy PID (IT2-FPID) lies in its ability to handle the high level of uncertainties rather than only having an extra degree of freedom provided by the Footprint of Uncertainty (FOU) on a highly nonlinear pH neutralization process. In order to illustrate the effect of the FOU on the control performance, the control performance of an IT2-FPID controller composed of 3×3 rules will be compared with a Type-1 Fuzzy PID (T1-FPID) controller of 5×5 rules. Moreover, in order to provide more extra degree of freedom to the T1-FPID structure, we will employ two self-tuning mechanisms where the weights of the fuzzy rules are adjusted in an online manner. Thus, we will present detailed comparative studies on how the extra degrees of freedom provided by the FOU or the employed tuning mechanisms affect the control and robustness performance. The presented analysis confirm that by tuning the FOU the performance of the IT2-FPID is better in wide range of operating points in comparison with its type-1 and self-tuning type-1 fuzzy counterparts which is not merely for the IT2-FPID use of extra parameters, but rather its different way of dealing with the disturbance, nonlinearities uncertainties and noise.
  • Keywords
    chemical engineering; control system synthesis; fuzzy control; pH control; three-term control; FOU; IT2-FPID controller; T1-FPID controller; control performance; footprint-of-uncertainty; fuzzy rules; interval type-2 fuzzy PID controller; online rule weighing based type-1 fuzzy PID controller; pH neutralization process; proportional-integral-derivative controller; self-tuning mechanisms; Noise; Process control; Robustness; Trajectory; Tuning; Uncertainty; Interval type-2 fuzzy PID controllers; extra degress of freedom; pH neutralization model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891627
  • Filename
    6891627