DC motorun bulanık mantık denetleyici kullanarak gerçek zamanda hız denetimi

Yıl 2017, Cilt: 23 Sayı: 5, 543 - 549, 20.10.2017

İsmet Kandilli

Öz

Bu çalışmada, DC motorun gerçek zamanda farklı
yükler altında hız kontrolü gerçekleştirilmiştir. Burada kontrolör olarak
Bulanık Mantık Denetleyici kullanılmıştır. Motor hız bilgisi takometre ile
ölçülen sistemde veri toplama kartı olarak NI USB-6218 DAQ kullanılmıştır.
Bulanık Mantık Denetim MATLAB^® ortamında gerçekleştirilmiştir. DC motor yüksüz, yarım yük ve tam yük olmak üzere farklı yükler altında
çalıştırılarak, hızın istenen değerde sabit kaldığı gözlemlenmiştir. Benzetim
sonuçları, gerçek zamanda denetim sonuçları ile karşılaştırılmıştır. Gerçek
zamanda bulanık denetim yük durumlarında daha iyi performans sağlamıştır.

Anahtar Kelimeler

DC motor, Bulanık mantık, Gerçek zamanlı sistem

Real-time speed controlling of a DC motor using fuzzy logic controller

Öz

The
current study analyzed real-time speed control of a DC motor under various
loads by using a Fuzzy Logic Controller (FLC). NI USB-6218 DAQ was preferred as
the data card for the system measuring the speed of the motor by a tachometer.
Fuzzy logic control was employed by means of MATLAB^®. The speed was
controlled to remain constant by operating the DC motor under various loads as no-loaded,
half loaded, and full loaded. Simulation results are compared with the results
of real-time control. The real-time fuzzy control provided good speed tracking
performance in load conditions.

Anahtar Kelimeler

DC motors, Fuzzy logic, Real-time system

Kaynakça

• Liu ZZ, Luo FL, Rashid MH. “Speed nonlinear control of dc motor drive with field weakening”. IEEE Transactions Industry Application, 39(2), 417-423, 2003.
• Drainkov D, Hellendoorn H, Reinfrank M. An Introduction to Fuzzy Control. Berlin Heidelberg, New York, USA, Springer-Verlag, 1993.
• Tipsuwan Y, Mo-Yuen C. “Fuzzy logic microcontroller implementation for DC motor speed control”. IEEE the 25th Annual Conference IECON '99, California, USA, 29 November-3 December 1999.
• Malhotra R, Kaur T, Deol GS. “DC motor control using fuzzy logic controller”. International Journal of Advanced Engineering Sciences and Technologies, 8, 291-296, 2011.
• Thepsatom P, Numsomran A, Tipsuwanporn V, Teanthong T. “DC motor speed control using fuzzy logic based on labview”. IEEE International Joint Conference SICE-ICASE, Busan, South Korea, 18-21 October 2006.
• Pavankumar SVSR, Krishnaveni S, Venugopal YB, Babu YSK. “A neuro-fuzzy based speed control of separately excited DC motor”. International Conference on Computational Intelligence and Communication Networks, Bhopal, India, 26-28 November 2010.
• Jang JO. “A deadzone compensator of a dc motor system using fuzzy logic control”. IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews, 31(1), 42-48, 2001.
• Shi A, Yan M, Li J, Xu W, Shi Y. “The research of fuzzy PID control application in DC motor of automatic doors”. IEEE International Conference on Electrical and Control Engineering, Yichang, China, 16-18 September 2011.
• Alyaqout SF, Papalambros PY, Ulsoy AG. “Combined robust design and robust control of an electric DC motor”. IEEE/ASME Transactions on Mechatronics, 16(3), 574-582, 2011.
• Shi Y, Huang J, Yu B. “Robust tracking control of networked control systems: Application to a networked DC motor”. IEEE Transactions on Industrial Electronics, 60(12), 5864-5874, 2013.
• Li Z, Chen J, Zhang G, Gan MG. “Adaptive robust control for dc motors with ınput saturation”. IET Control Theory & Applications, 5(16), 1895-1905, 2011.
• Kim SH, Ishiyama K. “Hybrid speed control of a DC motor for magnetic wireless manipulation based on low power consumption: Application to a magnetic wireless blood pump”. IEEE Transactions on Magnetics, 50(4), 1-7, 2014.
• Yao J, Jiao Z, Ma D. “Adaptive robust control of DC motors with extended state observer”. IEEE Transactions on Industrial Electronics, 61(7), 3630-3637, 2014.
• Castaneda CE, Loukianov AG, Sanchez EN, Toledo BC. “Discrete-Time neural sliding-mode block control for a DC motor with controlled flux”. IEEE Transactions on Industrial Electronics, 59(2), 1194-1207, 2012.
• Rubaai A, Kotaru R. “Online identification and control of a DC motor using learning adaptation of neural networks”. IEEE Transactions on Industry Applications, 36(3), 935-942, 2000.
• Li H, Chow MY, Sun Z. “EDA-Based speed control of a networked DC motor system with time delays and packet losses”. IEEE Transactions on Industrial Electronics, 56(5), 1727-1735, 2009.
• Ramirez H S, Salazar MAO. “On the robust control of buck-converter DC-Motor combinations”. IEEE Transactions on Industrial Electronics, 28(8), 3912-3922, 2013.
• Liu ZZ, Luo FL, Rashid MH. “Speed nonlinear control of DC Motor drive with field weakening”. IEEE Trans. on Industry Applications, 39(2), 417-423, 2003.
• Fallahi M, Azadi S. “Robust control of DC motor using fuzzy sliding mode control with PID compensator”. The International Multi Conference of Engineers and Computer Scientists IMECS, Hong Kong, 18-20 March 2009.
• Ang KH. Evolutionary Learning and Global Search for Multi-Optimal PID Tuning Rules, Ph.D. Thesis, Glasgow University, Glasgow, UK, 2005.
• Yager RR, Filev DP. Essentials of Fuzzy Modeling and Control, Canada, Wiley, 1994.
• Muruganandam M, Madheswaran M. “Modeling and simulation of modified fuzzy logic controller for various types of DC motor drives”. International Conference on Control, Automation, Communication and Energy Conservation, Perundurai, Tamilnadu, India, 4-6 June 2009.
• Sousa GCD, Bose BK. “A fuzzy set theory based control of a phase-controlled converter DC machine drive”. Conference Record of the 1991 Industry Applications Society Annual Meeting, Dearborn, USA, 28 September-4 October 1991.