A Comparative Real-Time Speed Control of PMSM with Fuzzy Logic and ANN Based Vector Controller

Yıl 2019, Cilt: 1 Sayı: 1, 123 - 143, 30.06.2019

Ezgi Güney Serap Karagöl Memnun Demir

Öz

This paper presents, analyzed real-time speed control of
Permanent Magnet Synchronous Motor (PMSM) under constant load by using Fuzzy
Logic (FL) controller and recurrent Artificial Neural Network (ANN) controller.
A closed loop PMSM drive system is improved using the mathematical model of the
PMSM in Matlab / Simulink. Two types of controllers are used; the first
controller is the real-time FL controller and the second controller is a
real-time recurrent ANN controller in terms of smoother speed response. Whole
drive systems is simulated in Matlab/Simulink program. The simulation results
show that the focused ANN controller produce considerable control performance
compare to the FL controller on controlling speed reference variations

Anahtar Kelimeler

Permanent magnet synchronous motor; artificial neural network; fuzzy logic; real-time control.

SMSM'nin Bulanık Mantık ve YSA Tabanlı Vektör Kontrol Yöntemi ile Karşılaştırmalı Gerçek Zamanlı Hız Kontrolü

Öz

Bu
çalışmada, Bulanık Mantık (BM) ve tekrarlayan Yapay Sinir Ağı (YSA) kontrol
ünitesi kullanılarak Sabit Mıknatıslı Senkron Motorunun (SMSM)sabit yük altında
gerçek zamanlı hız kontrolü sunulmaktadır. SMSM’ nin matematiksel modeli
kullanılarak Matlab / Simulink’te kapalı çevrim PMSM tahrik sistemi
geliştirilmiştir. İki tip kontrolör kullanılmıştır; birinci denetleyici, gerçek
zamanlı BM denetleyicisi ve ikinci denetleyici, daha yumuşak hız tepkisi
açısından gerçek zamanlı bir tekrarlayan YSA denetleyicisidir. Tüm tahrik
sistemleri Matlab / Simulink programında simüle edilmiştir. Simülasyon
sonuçları, odaklanmış YSA kontrolörünün, hız referansı değişikliklerini kontrol etmede BM
kontrolörüne kıyasla önemli kontrol performansı sağladığını göstermektedir.

Anahtar Kelimeler

Sürekli mıknatıslı senkron motor; yapay sinir ağları; bulanık mantık; gerçek zamanlı kontrol.

Kaynakça

• Arroyo, E. L. C. (2006). Modeling and simulation of permanent magnet synchronous motor drive system. University of puerto rico, Mayagüez Campus.
• Asri, A., Samat, A., & Fazli, M. N. (2017). Regular paper Speed Control Design of Permanent Magnet Synchronous Motor using Takagi-Sugeno Fuzzy Logic Control. J. Electrical Systems, 13(4), 689-695.
• Birou, I. M., Rusu, C. C., Pavel, S. G., & Maier, V. (2014, October). Real-time robust controlled driving system with permanent-magnet synchronous motor. In 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), pp: 921-926. Chaoui, H., & Sicard, P. (2012). Adaptive fuzzy logic control of permanent magnet synchronous machines with nonlinear friction. IEEE Transactions on Industrial Electronics, 59(2), 1123-1133 Gieras, J. F. (2009). Permanent magnet motor technology: design and applications. CRC press.Goh, S. L., & Mandic, D. P. (2004). A complex-valued RTRL algorithm for recurrent neural networks. Neural computation, 16(12), 2699-2713.
• Guney, E., Dursun, M., & Demir, M. (2017, January). Artificial neural network based real time speed control of a linear tubular permanent magnet direct current motor. In 2017 International Conference on Control, Automation and Diagnosis (ICCAD) (pp. 540-544). IEEE.
• Habbi, H. M. D., & Rashed, S. T. (2016). PI and Fuzzy Speed Controllers for PM Synchronous Motor Drive. International Journal of Computer Applications, 149(1).
• Harahap, C. R., Saito, R., Yamada, H., & Hanamoto, T. (2014). Speed control of permanent magnet synchronous motor using FPGA for high frequency SiC MOSFET inverter. Journal Engineering Science and Technology, pp:11-20.
• Hasanien, H. M. (2011). FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives. Energy Conversion and Management, 52(2), 1252-1257.
• Jayalakshmi, T., & Santhakumaran, A. (2011). Statistical normalization and back propagation for classification. International Journal of Computer Theory and Engineering, 3(1), 1793-8201. Kaur, S., & Bharti, G. (2012). Two inputs two output fuzzy controller system design using MATLAB. Int. J. Adv. Eng. Sci. Technol.(IJAEST), 2(3).
• Krishnan, R. (2009). Permanent magnet synchronous and brushless DC motor drives. CRC press.Kumar, P., & Tomer, A. S. (2013). Modeling & Simulation of PMSM Drives with Fuzzy Logic Controller, 3(4), 2492-2497.
• Kumari, N. K. (2015). Field Oriented Control of PMSM with Model Reference Adaptive Control Using Fuzzy-PI Controller,8(1), 96-108.
• Liu, T., Chen, G., & Li, S. (2014). Application of Vector Control Technology for PMSM Used in Electric Ve-hicles. Open Automation and Control Systems Journal, 6, 1334-1341.
• Perera, C. (2002) Sensorless control of permanent-magnet synchronous motor drives, Doctor of Philosophy, Aalborg University.
• Pewmaikam, C., Srisertpol, J., & Khajorntraidet, C. (2012). Adaptive fuzzy logic compensator for permanent magnet synchronous motor torque control system. International Journal of Modeling and Optimization, 2(2), 141.
• Plangklang, B., Kantawong, S., & Noppakant, A. (2013). Study of generator mode on permanent magnet synchronous motor (PMSM) for application on elevator energy regenerative unit (EERU). Energy Procedia, 34, 382-389.Qutubuddin, M. D., & Yadaiah, N. (2017). Modeling and implementation of brain emotional controller for Permanent Magnet Synchronous motor drive. Engineering Applications of Artificial Intelligence, 60, 193-203.
• Rajasekhar, A., Jatoth, R. K., & Abraham, A. (2014). Design of intelligent PID/PIλDμ speed controller for chopper fed DC motor drive using opposition based artificial bee colony algorithm. Engineering Applications of Artificial Intelligence, 29, 13-32.
• Reddy, B. L., Anjaiah, U., & Rao, T. S. (2016). A Closed Loop Speed Control of PMSM Drive Using Fuzzy Logic Controller. ImperialJournal of Interdisciplinary Research (IJIR), 2(6).
• Štulrajter, M., Hrabovcova, V., & Franko, M. (2007). Permanent magnets synchronous motor control theory. Journal of electrical engineering, 58(2), 79-84.
• Thampatty, K. S., & Raj, P. R. (2015). An Adaptive RTRL Based Neurocontroller for Damping Power System Oscillations. International Journal of Applied, 4(1), 1-12.
• Wilamowski, B. M. (2009). Neural network architectures and learning algorithms. IEEE Industrial Electronics Magazine, 3(4), 56-63.
• Xu, D., Zhang, S., & Liu, J. (2013). Very-low speed control of PMSM based on EKF estimation with closed loop optimized parameters. Isa Transactions, 52(6), 835-843.
• Yu, J. S., Kim, S. H., Lee, B. K., Won, C. Y., & Hur, J. (2007). Fuzzy-logic-based vector control scheme for permanent-magnet synchronous motors in elevator drive applications. IEEE transactions on Industrial Electronics, 54(4), 2190-2200.