Type-1 and Type-2 Fuzzy Logic and Sliding-Mode Based Speed Control of Direct Torque and Flux Control Induction Motor Drives – A Comparative Study

References

1. BujaGS,KazmierkowskiMP. DTC of pwm inverter-fed AC motors – a survey. IEEE Trans Ind Electron2004;54:744–57.10.1109/TIE.2004.831717Search in Google Scholar

2. BlaschkeF. The principle of field-orientation as applied to the transvector closed-loop control system for rotating-field machines. Siemens Rev1988;34:135–47.Search in Google Scholar

3. TakahashiI,NoguchiT. A new quick response and high efficiency control strategy of an induction motor. IEEE Trans Ind Appl1986;22:820–27.10.1109/TIA.1986.4504799Search in Google Scholar

4. LinF, ShiehH, ShyuK,HuangP. Online gain tuning IP controller using realcoded genetic algorithm. J Electric Power Syst Res2004;72:157–69.10.1016/j.epsr.2004.03.013Search in Google Scholar

5. GadoueSM, GiaourisD,FinchJW. Tuning of PI speed controllerin DTC of induction motor based on genetic algorithms and fuzzy logic schemes. Proceedings of the 5th International Conference on Technology and Automation, 2005:85–90.Search in Google Scholar

6. LascuC, BoledeaI,BlaabjergF. Direct torque control of sensorless induction motor drives: a sliding-mode approach. IEEE Trans Ind Appl2004;40:582–90.10.1109/TIA.2004.824441Search in Google Scholar

7. UddinMN, RadwanTS,RahmanM. Performance of fuzzy-logic-based indirect vector control for induction motor drive. IEEE Trans Ind Appl2002;38:1219–25.10.1109/TIA.2002.802990Search in Google Scholar

8. BarreroF, GonzalezA, TorralbaA, GalvanE,FranqueloLG. Speed control of induction motors using a novel fuzzy sliding mode structure. IEEE Trans Fuzzy Syst2002;10:375–83.10.1109/TFUZZ.2002.1006440Search in Google Scholar

9. OhW, KimY, KimC, KwonT,KimH. Speed control of induction motor using genetic algorithm based fuzzy controller. Proceedings of the IECON’99, 1999;2:625–29.Search in Google Scholar

10. LuoY,ChenW. Sensorless stator field orientation controlled induction motor drive with a fuzzy speed controller. Comput Math Appl2012;64:1206–16.10.1016/j.camwa.2012.03.064Search in Google Scholar

11. FooG,RahmanMF. Direct torque and flux control of an IPM synchronous motor drive using a backstepping approach. IET Electric Power Appl2009;3:413–21.10.1049/iet-epa.2008.0182Search in Google Scholar

12. BarambonesO, GarridoAJ,, MasedaFJ. Integral sliding mode controller for induction motor based on FOC theory. IET Control Theory Appl2007;1:786–94.10.1049/iet-cta:20060239Search in Google Scholar

13. ZhangY, ZhuJ, XuW, HuJ, DorrellDG,ZhaoyZ. Speed sensorless stator flux oriented control of three-level inverter-fed induction motor drive based on fuzzy logic and sliding mode control. Proceedings in 36th Annual Conference on IEEE Industrial Electronics Society (IECON-2010), 2010:2932–37.10.1109/IECON.2010.5675064Search in Google Scholar

14. ChenC. Sliding mode controller design of induction motor based on space-vector pulse width modulation method. Int J Innovative Comput Inf Control2009;5:3603–14.Search in Google Scholar

15. MohantyKB. Sensorless sliding mode control of induction motor drives. Proceedings of IEEE TENCON 2008:1–6.10.1109/TENCON.2008.4766709Search in Google Scholar

16. OliveiraJB, AraujoAD,DiasSM. Controlling the speed of a three-phase induction motor using a simplified indirect adaptive sliding mode scheme. Control Eng Pract2010;18:577–84.10.1016/j.conengprac.2010.02.010Search in Google Scholar

17. GadoueSM, GiaourisD,FinchJW. MRAS sensorless vector control of an induction motor using new sliding-mode and fuzzy-logic adaptation mechanisms. IEEE Trans Energy Conversion2010;25:394–402.10.1109/TEC.2009.2036445Search in Google Scholar

18. LaiY,LinJ. New hybrid fuzzy controller for direct torque control induction motor drives. IEEE Trans Power Electron2003;18:1211–19.10.1109/TPEL.2003.816193Search in Google Scholar

19. BoseBK. Modern power electronics and AC drives. Prentice Hall, Upper Saddle River, NJ, 2002.Search in Google Scholar

20. SlotineJJE,LiW. Applied nonlinear control. Prentice Hall, Englewood Cliffs, New Jersey, 1991.Search in Google Scholar

21. MikkiliS,PandaAK. PI and fuzzy logic controller based 3-phase 4-wire shunt active filter for mitigation of current harmonics with Id-Iq control strategy. J Power Electron JPE2011;11:914–21.10.6113/JPE.2011.11.6.914Search in Google Scholar

22. GadoueSM, GiaourisD,FinchJW. Artificial intelligence-based speed control of DTC induction motor drives-a comparative study. Electric Power Syst Res2009;79:210–19.10.1016/j.epsr.2008.05.024Search in Google Scholar

23. HazzabA, BousserhaneIK,KamliM. Design of fuzzy sliding mode controller by genetic algorithms for induction machine speed control. Int J Emerg Electric Power Syst2004: Vol. 1:1016–27.10.2202/1553-779X.1016Search in Google Scholar

24. ZadehLA. The concept of a linguistic variable and its application to approximate reasoning. Inf Sci1975;8:199–249.10.1016/0020-0255(75)90036-5Search in Google Scholar

25. ZadehLA. Knowledge representation in fuzzy logic. IEEE Trans Knowl Data Eng1989;1:89–100.10.1109/69.43406Search in Google Scholar

26. KarnikNN,MendelJM. An introduction to type-2 fuzzy logic systems. Los Angeles, CA: University of Southern California, 1998.Search in Google Scholar

27. LiangQ,MendelJM. Interval type-2 fuzzy logic systems: theory and design. IEEE Trans Fuzzy Syst2000;8:535–50.10.1109/91.873577Search in Google Scholar

28. MendelJM, JohnRI,LiuF. Interval type-2 fuzzy logic systems made simple. IEEE Trans Fuzzy Syst2006;14:808–21.10.1109/TFUZZ.2006.879986Search in Google Scholar

29. MendelJM,JohnRI. Type-2 fuzzy sets made simple. IEEE Trans Fuzzy Syst2002;10:117–27.10.1109/91.995115Search in Google Scholar

30. CastroJR, CastilloO,MartinezLG. Interval type-2 fuzzy logic toolbox. Eng Lett2007;15:14.Search in Google Scholar