Tuncay YİĞİT, Çetin ELMAS, M. Ali AKCAYOL

Bulanık PI denetleyici ile anahtarlamalı relüktans motorun hız denetimi

Anahtarlamalı relüktans motor (ARM)’lar yapılarının basit ve rotor kayıplarının düşük olması nedeniyle endüstriyel uygulamalarda giderek artan bir ilgi görmektedir. Güç elektroniği ve bilgisayar teknolojisindeki gelişmelerin sonucunda ARM’lerin denetiminde başarılı çalışmalar yapılmıştır. ARM’lerin dinamik karakteristikleri, çalışma şartlarına bağlı olarak değişmektedir. Sabit kazanç katsayılarına sahip klasik PI denetleyici farklı hız ve yüklerde, özellikle hız değişimlerinde aşım ve dalgalanmalara neden olmaktadır. Bu makalede, ARM’nin hız denetimi için bir bulanık PI denetleyici önerilmiştir. Denetleyicide, bir bulanık mantık denetleyici (BMD)tarafından, PI denetleyicinin oransal ve integral katsayıları, motorun hız hatası ve hız hata değişimine bağlı olarak sürekli uyarlanmaktadır. Önerilen denetleyici TMS320F240 sayısal işaret işlemci (Sİİ) kullanılarak gerçekleştirilmiştir. Deneysel sonuçlardan, bulanık PI denetleyicinin farklı çalışma şartlarında klasik PI denetleyiciye göre daha iyi başarım sağladığı gözlemlenmiştir.

Fuzzy PI controller for speed control of switched reluctance motor

Switched reluctance motors (SRMs) have been increasingly used in industrial applications because of their simple structure and reduced rotor loses. As a result of improvement of power electronics and computer technology, there have been increased attentions to control the SRMs. Dynamic characteristics of SRMs are varying depending on working conditions. A PI (Proportional-Integral) controllers with constant gain values have overshoot and oscillations at varying speeds and load especially at transient-state. In this paper, a fuzzy PI controller was proposed to control the speed of the SRM. Proportional and integral gains of the PI controller are tuned by fuzzy logic controller (FLC) depending on speed error and change of the speed error. Fuzzy PI controller was implemented using TMS320F240 digital signal processor. Experimental results showed that fuzzy PI controller has better performance than a PI controller with a range of working conditions.

PDF

___

1. Bay, O.F., Elmas, C., “Modeling of the Inductance Variation and Control of the Switched Reluctance Motor Based on Fuzzy Logic”, Intelligent Automation and Soft Computing, 10(3), 233-246, 2004.
2. Lawrenson, P.J., Stephenson J.M., Blenkinsop,P.T., Corda, J., Fulton, N.N., “Variable-Speed Switched Reluctance Motors”, IEE Proceedings Part B, 127 (4), 253-265, 1980.
3. Miller, T.J.E., Stephenson, J.M., MacMinn S.R.,Handersot, J.R., “Switched Reluctance Drives”,IEEE Industry Applications Society, Tutorial Course, 1990.
4. Ziegler, J.G., Nichols, N.B., “Optimum Settings for Automatic Controllers”, Transactions of ASME,64, 759-768, 1942.
5. Akcayol, M.A., Bir Anahtarlamalı Relüktans Motorun Sinirsel-Bulanık Denetimi, Doktora Tezi, Gazi Üniversitesi, Ankara, 2001.
6. Cheock, A.D., Ertugrul, N., “Use of Fuzzy Logic for Modeling, Estimation, and Prediction in Switched Reluctance Motor Drives”, IEEE Transactions on Industarial Electronics, 46(6),1207-1224, 1999.
7. Buja, G.S., “Variable Structure Control of a SRM Drive”, IEEE Transactions on Industrial Electronics, 40(1), 56-63, 1993.
8. Zhu, X.M., Panda, S.K., Dash, P.K., Tan, S.H., “Experimental Investigation of Variable Structural PID Control for Switched Reluctance Motor Drives”, Proceedings of 1997 International Conf. on Power Electronics and Drive Systems, 1, 205-210, 1997.
9. Ho, W.K., Panda, S.K., Lim, K.W., Huang, F.S., “Gain-Scheduling Control of the Switched Reluctance Motor”, Control Engineering Practice,6, 181-189, 1998.
10. Fung, H.W., Wang, Q.G., Lee, T.H., “PI Tuning in Terms of Gain and Phase Margins”, Automatica,34(9), 1145-1149, 1998.
11. Spong, M.I., Marino, R., Peresada, S.M., Taylor, D.G., “Feedback Linearization Control of a Switched Reluctance Motor”, IEEE Transactions on Automatic Control, AC-32(5), 371-379, 1987.
12. Haiqing, Y., Panda, S.K., Liang, Y.C., “Sliding Mode Control of Switched Reluctance Motors: An Experimental Investigation”, Proceedings of IECON, 96-101, 1996.
13. Elmas, Ç., Bay, Ö.F., “Modeling and Operation of A Nonlinear Switched Reluctance Motor Drive Based on Fuzzy Logic”, EPE’95, Sevilla, 592-597,1995.
14. Ramamurthy, S.S., Balda, J.C., Implementation of Neural Networks To Aid Switched Reluctance Motor Control on the TMS320C6701, Texas Instruments, Application Report, 2000.
15. Berger, M., “Self-tuning of a PI Controller Using Fuzzy Logic for A Construction Unit Testing Apparatus”, Control Engieneering Practice, 4(6), 785-790, 1996.
16. Zhao, Z.Y., Tomizuka, M., Isaka, S., “Fuzzy Gain Scheduling of PID Controllers”, IEEE Transac-tions on Systems, Man, and Cybernetics, 23(5), 1392-1398, 1993.
17. Chen, C.G. and Liu, T.H., “Nonlinear Controller Design for Switched Reluctance Drive Systems”,IEEE Transactions on Aerospace and Electronic Systems, 39(4), 1429-1440, 2003.
18. TMS320F240 DSP Controllers Evaluation Module, Texas Instruments, 1999.
19. Motto, E.R., Hybrid Circuits Simplify IGBT Module Gate Drive, Powerex Inc., Youngwood,PA, USA, 1999.