Speed Control of DC Motor Using Interval Type-2 Fuzzy Logic Controller

Direct current (DC) motors are considerably utilized in many implementations requiring speed and position controls. The simplicity of DC motor speed control is also the main reason for its widespread use. Recently, with rapid developments in power electronics, microprocessors and semiconductor materials, many control structures are designed for DC motors. In this study, the speed control of the DC motor is carried out using Matlab/Simulink package program. Type-2 Fuzzy Logic controller (T2FLC) that has efficient performance in modelling uncertainties is proposed for DC motor speed control. The classical Proportional+Integral (PI) controller and T2FLC are connected to the speed control unit of DC motor. Simulation studies have also been realized under several operating conditions such as tracking reference speeds and load changes. According to the obtained simulation results, it has been observed that T2FLC has better results than the classical PI controller in operating conditions.

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G. G. Rigatos, “Adaptive fuzzy control of DC motors using state and output feedback”, Electric Power Systems Research, vol. 79, no. 11, pp. 11-23, pp. 1579–1592, 2009.

J. Reyes, C.M. Astorga-Zaragoza, M. Adam-Medina, G.V. Guerrero- Ramírez, “Bounded neuro-control position regulation for a geared DC motor”, Engineering Applications of Artificial Intelligence , vol. 23, no. 8, pp. 1398-1407, 2010.

K. Nouri, R. Dhaouadi, N.B. Braiek, “Adaptive control of a nonlinear DC motor drive using recurrent neural networks”, Applied Soft Computing, vol. 8, pp. 371-382, 2008.

A. Gani, H.R. Özçalık, H. Açıkgöz, Ö.F. Keçecioğlu, E. Kılıç, “Farklı Kural Tabanları Kullanarak PI-Bulanık Mantık Denetleyici ile Doğru Akım Motorunun Hız Denetim Performansının İncelenmesi”, Academic Platform Journal of Engineering and Science, vol. 2, no. 1, pp. 16-23, 2014.

C.F. Hsu, B.K. Lee, “FPGA-based adaptive PID control of a DC motor driver via sliding-mode approach”, Expert Systems with Applications, vol. 38, no. 9, pp.11866-11872, 2011.

Kiruthika, A.A. Rajan, and P. Rajalakshmi, “Mathematical modelling and speed control of a sensored brushless DC motor using intelligent controller,” International Conference on Emerging Trends in Computing, Communication and Nanotechnology, pp.211–216, 2013

R. A. Kiruthika, T. Ramesh, “Speed control of a sensored brushless DC motor using FLC”, Int. J. Eng. Res. Technol., vol. 3, no. 4, pp. 2159-2162, 2014.

J. G. Ziegler, N. B Nichols, “Optimum settings for Automatic Controllers”, Trans. ASME, vol. 64, pp. 759-768, 1942.

L. A. Zadeh, “Fuzzy Sets”, Information and Control, vol. 8, pp. 335- 353, 1965.

L. A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning”, Information sciences, vol. 8, no. 3, pp. 199-249, 1975.

K. Tai, A. R., El-Sayed, M., Biglarbegian, C.I., Gonzalez, O., Castillo, S., Mahmud, “Review of Recent Type-2 Fuzzy Controller Applications”, Algorithms, vol. 9, no. 2, pp. 1-19, 2016.

J. M. Mendel, R.I. John, “Type-2 fuzzy sets made simple”, IEEE Transactions on Fuzzy Systems, vol. 10, no. 2, pp. 117-127, 2002.

A. Rahib Hidayat, O. Kaynak, “Type 2 fuzzy neural structure for identification and control of time-varying plants”, IEEE Transactions on Industrial Electronics, vol. 57, no. 12, pp. 4147-4159, 2010.

K. Tufan, E. Ibrahim, G. Mujde, Y. Engin, “Type-2 fuzzy model based controller design for neutralization processes”, ISA Transactions, vol. 51, no. 2, pp. 277-287, 2012.

Q. Liang, J.M. Mendel, “Interval type-2 fuzzy logic systems: theory and design”, IEEE Transactions on Fuzzy Systems, vol. 8, no. 5, pp. 535-550, 2000.

F. Mohsen, B.Z. Amir Reza, E. Mohammad, “Intelligent control of a DC motor using a self-constructing wavelet neural network”, Systems Science & Control Engineering, vol. 2, pp. 261-267, 2014.

Ö. İlker Ali, S. İsmail, H. Saadetdin, “The Control of a DC Motor By Fuzzy Logic Controller”, e-Journal of New World Sciences Academy, vol. 6, no. 2, pp. 533-541, 2011.

V. Akash, G. Deeksha, D. Bharti, “Speed response of brushless DC motor using fuzzy PID controller under varying load condition”, Journal of Electrical Systems and Information Technology, vol. 4, no.2, pp. 310-321, 2017.

B. Bharat, S. Madhusudan, Adaptive control of DC motor using bacterial foraging algorithm, Applied Soft Computing, vol. 11, no. 8, pp. 4913–4920, 2011.

M. Gökbulut, B. Dandil, C. Bal, “Development and Implementation of a Fuzzy-Neural Network Controller for Brushless DC Drives”, Intelligent Automation & Soft Computing, vol. 13, no. 4, pp. 415-427, 2007.

H. Açıkgöz, Ö.F. Keçecioğlu, A. Gani, M. Şekkeli, “Lineer Kuadratik Regülatör ve Genetik Tabanlı PID Denetleyici ile Doğru Akım Motorunun Hız Denetimi”, International Conference and Exhibition on Electronic, Computer and Automation Technologies (ICEECAT’14), May 9-11,2014 Konya, Turkey

S. Joice, P. Nivedhitha, “Simulation of speed control of brushless DC motor with fuzzy logic controller,” International Journal of Electrical, Electronics and Data Communication, vol. 2, no. 4, pp. 24-29, 2014.

A. Gani, H. Açıkgöz, Ö.F. Keçecioğlu, M. Şekkeli, “Examine of Speed Control Performance of Permanent Magnet DC Motor with PI- Fuzzy Logic Controller by Using Different Membership Functions” 7th International Advanced Technologies Symposium (IATS’13), 30 October-1 November 2013, Istanbul, Turkey.

H. Hassani, J. Zarei, “Interval Type-2 Fuzzy Logic Controller Design for the Speed Control of DC Motors”, Systems Science & Control Engineering, vol.3 no. 1, pp. 266-273, 2015.

H. Acikgoz, O.F. Kececioglu, A. Gani, M. Tekin, M. Sekkeli, “Robust Control Of Shunt Active Power Filter Using Interval Type-2 Fuzzy Logic Controller For Power Quality Improvement”, Tehnički vjesnik, vol. 24, no. Suppl. 2, pp. 363-368, 2017.