Aralık değerli tip-2 bulanık PID kontrolörler ve bir çevrimiçi öz-ayarlama mekanizması

Bu çalışmada, Aralık değerli tip-2 bulanık PID (ADT2-BPID) kontrolörlerin içyapıları incelenmiş olup ve de yeni bir öz-ayarlama önerilmiştir. Bu amaçla ilk olarak geleneksel yani tip-1 bulanık PID (T1-BPID) kontrolörler ile ADT2-BPID kontrolörlerin yapısal özellikleri ve tasarım parametreleri incelenmiştir. T1-BPID kontrolörler için önerilmiş olan bir öz-ayarlama yöntemi olan fonksiyon tabanlı öz-ayarlama yöntemi ADT2-BPID kontrolör yapılarına uygulanmıştır. Bu öz ayarlama yöntemi yardımıyla ADT2-BPID kontrolörün ölçekleme çarpanlarının çevrimiçi ayarlanabileceği gösterilmiştir. Önerilen öz-ayarlamalı ADT2-BPID tasarımında sırasıyla T1-BPID, ADT2-BPID kontrolörleri tasarlanmıştır. Benzetim çalışmasında önerilen öz-ayarlamalı yapı tip-1 ve aralık değerli tip-2 eşdeğerleriyle doğrusal olmayan bir konik tank sistemi üzerinde karşılaştırılmıştır. Önerilen öz ayarlamalı ADT2-BPID kontrolör yapısı ile hem ADT2-BPID kontrolör içyapısından gelen fazladan serbestlik derecesi hem de fonksiyon ayarlayıcı tabanlı öz ayarlama yöntemi sayesinde tip-1 bulanık ve tip-2 bulanık eşdeğerlerine kıyasla daha iyi sonuçlar vermiştir.

Interval type-2 fuzzy PID controllers and an online self-tuning mechanism

In this study, the general structure of interval type-2 fuzzy PID (IT2-FPID) controllers and a self-tuning mechanism for IT2-FPID controller is presented. In this context, we will present and examine the controller structures of the type-1 fuzzy PID (T1-FPID) and IT2-FPID controllers on a generic a symmetrical 3x3 rule base. Then, an online self-tuning mechanism for IT2-FPID controllers is presented. The presented self-tuning mechanism, which was firstly presented for T1-FPID, controllers, tunes the scaling factors of IT2-FPID with respect to the current error value of the control system.  A systematic design approach has been also presented for the self-tuning IT2-FPID structure. The performance of the T1-FPID, IT2-FPID and Self-Tuning IT2-FPID structures has been investigated on a simulation study conducted on a nonlinear tank system. The results have shown that, since the proposed approach has more extra degree of freedom provided by its interval type-2 fuzzy sets and self-tuning mechanism, the self-tuning IT2FPID resulted with a superior control performance in comparison with its type-1 and interval type-2 counterparts.

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  • Galichet S, Foulloy L. “Fuzzy controllers: synthesis and equivalences”. IEEE Transactions on Fuzzy Systems, 3(2), 140–148, 1995.
  • Huang TT, Chung HY, Lin JJ. “A fuzzy PID controller being like parameter varying PID”. IEEE International Conference on Fuzzy Systems, Seul, South Korea, 22-25 August 1999.
  • Qiao WZ, Mizumoto M. “PID type fuzzy controller and parameters adaptive method”. Fuzzy Sets and Systems, 78(1), 23–35, 1996.
  • Li HX, Gatland HB. “Conventional fuzzy control and its enhancement”. IEEE Transactions on Systems, Man and Cybernetics Part B, 26(5), 791–797, 1996.
  • Duan XG, Li HX, Deng H. “Effective tuning method for fuzzy PID with internal model control”. Industrial & Engineering Chemistry Research, 47, 8317–8323, 2008.
  • Hu B, Mann GKI, Gasine RG. “New methodology for analytical and optimal design of fuzzy PID controllers”. IEEE Transactions on Fuzzy Systems, 7(5), 521–539, 1999.
  • Mudi RK, Pal NR. “A robust self-tuning scheme for PI- and PD-type fuzzy controllers”. IEEE Transactions on Fuzzy Systems, 7(1), 2–16, 1999.
  • Woo ZW, Chung HY, Lin JJ. “A PID-type fuzzy controller with self-tuning scaling factors”. Fuzzy Sets and Systems, 115, 321–326, 2000.
  • Ahn KK, Truong DQ. “Online tuning fuzzy PID controller using robust extended Kalman filter”. Journal of Process Control, 19, 1011–1023, 2009.
  • Karasakal O, Guzelkaya M, Eksin I, Yesil E, Kumbasar T. “Online tuning of fuzzy PID controllers via rule weighting based on normalized acceleration”. Engineering Applications of Artificial Intelligence, 26(1), 184-197, 2013.
  • Wu D, Tan WW. “Interval Type-2 Fuzzy PI Controllers: Why They Are More Robust”. IEEE International Conference on Granular Computing, San Jose, USA, 14-16 August 2010.
  • Wu D. “On the Fundamental Differences between Type-1 and Interval Type-2 Fuzzy Logic Controllers”. IEEE Transactions on Fuzzy Systems, 20(5), 832–848, 2012.
  • Hagras H. “A Hierarchical Type-2 Fuzzy Logic Control Architecture for Autonomous Mobile Robots”. IEEE Transactions on Fuzzy Systems, 12(4), 524–539, 2004.
  • Kumbasar T. “A simple design method for interval type-2 fuzzy PID controllers”. Soft Computing, 18(7), 1293–1304, 2014.
  • Yesil E. “Interval type-2 fuzzy PID load frequency controller using Big Bang-Big Crunch optimization”. Applied Soft Computing, 15, 100–112, 2014.
  • Kumbasar T, Hagras H. “Big Bang–Big Crunch optimization based interval type-2 fuzzy PID cascade controller design strategy”. Information Sciences, 282, 277–295, 2014.
  • Kumbasar T, Hagras H. An Overview on Interval Type-2 Fuzzy PID Controllers. Editors: Kacprzyk J, W. Pedrycz W. Handbook of Computational Intelligence, 285-293, Berlin, Germany, Springer-Verlag, 2015.
  • Castillo O, Melin P. Type-2 Fuzzy Logic Theory and Applications, Berlin, Germany, Springer-Verlag, 2008.
  • Kumbasar T, Hagras H. “A Self-Tuning zSlices based General Type-2 Fuzzy PI Controller“. IEEE Transactions on Fuzzy Systems, 23(4), 991-1013, 2015.
  • Kumbasar T, Hagras H. “A Gradient Descent Based Online Tuning Mechanism for PI Type Single Input Interval Type-2 Fuzzy Logic Controllers”. IEEE International Conference on Fuzzy Systems, Istanbul, Turkey, 2-5 August 2015.
  • Liang Q, Mendel JM. “Interval type-2 fuzzy logic systems: theory and design”. IEEE Transactions on Fuzzy Systems, 8(5), 535–550, 2000.
  • Taskin A, Kumbasar T. “An open source Matlab/Simulink Toolbox for Interval Type-2 Fuzzy Logic Systems”. IEEE Symposium Series on Computational Intelligence, Cape Town, South Africa, 7-10 December 2015.