In this study, the position of DC machines has been controlled by PID (Proportional-Integral-Derivative) algorithm, has been trained by ANFIS (Adaptive Neuro Fuzzy Inference System) algorithm and output equations for different inputs have been obtained. Control mechanisms have been explained by comparing graphs that are obtained from the two algorithms.
[1] ST, AN280. Application note controlling voltage transiensts in full bridge driver applications.
[2] Klee Andrew, “Development of a speed control system using matlab and simulink, implemented with a digital signal processor”, Master of Science in the Department of Electrical and Computer Engineering - In the College of Engineering and Computer Science at the University of Central Florida, Orlando, Florida, Spring Term, 2005
[3] TMS320F2810, TMS320F2811, TMS320F2812, TMS320C2810, TMS320C2811, TMS320C2812, Digitalsignal processors, data manual. literature number: SPRS174L. April 2001 − Revised December 2004
[4] Maas, J., “Industrial Electronics”, Prentice-Hall, New Jersey, 844-860 (1995)
[5] MATLAB Fuzzy Logic Toolbox-2 User’s Guide, COPYRIGHT 1995–2007 The MathWorks, Inc.
[6] J.-S. R. Jang, C.-T. Sun ve E. Mizutani, Neuro-fuzzy and soft computing, Prentice Hall, New Jersey, 1997.
Bu çalışmada, doğru akım (DC) makinaların konumu PID (Proportional-Integral-Derivative) algoritması kullanılarak denetlenmiş, ANFIS (Adaptive Neuro Fuzzy Inference System) kullanılarak eğitimi yapılmış ve farklı girdiler için çıktı denklemleri elde edilmiştir. Her iki algoritmadan elde edilen sonuç grafikleri karşılaştırılarak denetim yöntemleri hakkında açıklamalar yapılmıştır.
[1] ST, AN280. Application note controlling voltage transiensts in full bridge driver applications.
[2] Klee Andrew, “Development of a speed control system using matlab and simulink, implemented with a digital signal processor”, Master of Science in the Department of Electrical and Computer Engineering - In the College of Engineering and Computer Science at the University of Central Florida, Orlando, Florida, Spring Term, 2005
[3] TMS320F2810, TMS320F2811, TMS320F2812, TMS320C2810, TMS320C2811, TMS320C2812, Digitalsignal processors, data manual. literature number: SPRS174L. April 2001 − Revised December 2004
[4] Maas, J., “Industrial Electronics”, Prentice-Hall, New Jersey, 844-860 (1995)
[5] MATLAB Fuzzy Logic Toolbox-2 User’s Guide, COPYRIGHT 1995–2007 The MathWorks, Inc.
[6] J.-S. R. Jang, C.-T. Sun ve E. Mizutani, Neuro-fuzzy and soft computing, Prentice Hall, New Jersey, 1997.
Gün, A. (2007). THE POSITION CONTROL OF THE DC MACHINE BY PID ALGORITM AND TRAINING WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM. Journal of Science and Technology of Dumlupınar University(014), 55-64.