CFP last date
20 December 2024
Reseach Article

Design of Intelligent Controller for Chaotic Permanent Synchronous Motor

by Negar Etemadi, Assef Zare
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 166 - Number 7
Year of Publication: 2017
Authors: Negar Etemadi, Assef Zare
10.5120/ijca2017914070

Negar Etemadi, Assef Zare . Design of Intelligent Controller for Chaotic Permanent Synchronous Motor. International Journal of Computer Applications. 166, 7 ( May 2017), 23-27. DOI=10.5120/ijca2017914070

@article{ 10.5120/ijca2017914070,
author = { Negar Etemadi, Assef Zare },
title = { Design of Intelligent Controller for Chaotic Permanent Synchronous Motor },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 166 },
number = { 7 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume166/number7/27683-2017914070/ },
doi = { 10.5120/ijca2017914070 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:13:05.253438+05:30
%A Negar Etemadi
%A Assef Zare
%T Design of Intelligent Controller for Chaotic Permanent Synchronous Motor
%J International Journal of Computer Applications
%@ 0975-8887
%V 166
%N 7
%P 23-27
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an intelligent controller design method for the chaotic permanent magnet synchronous motor stability is presented. Active control strategy is a powerful control technique in stability chaotic systems. Learning algorithm using active control techniques, and then intelligent controller will be used. The proposed method can reduce the dimensions of the controller. A comparative study has been one with active and adaptive neural fuzzy controller. Simulation results show that the proposed controller can be chaotic permanent magnet synchronous motor will converge to the unstable equilibrium points. The controller can zero error, while has been tracking well desired value.

References
  1. T. Matsumoto, L. O. Chua and M. Komuro, (1985). The double scroll. IEEE Trans. Circuit syst, vol 32, p. 797-818
  2. J. P. Eckmann, and D. Rulle, (1985) Ergodic theory of chaos and strange attractors, Rev. Mod. Phys, vol. 75, no. 3, p. 617-656
  3. L. O. Chua, M. Komuro and T. Matsumoto, (1986) The double scroll family, IEEE Trans. Circuit Syst, vol. 33, p. 1072-118
  4. Ott E, Grebogi C, Yorke JA. (1990), Controlling Chaos. Phys Rev Lett; vol. 64, p. 1196–9
  5. Du Qu Wei, Xiao Shu Luo, (2007) , “Passivity-based adaptive control of chaotic oscillations in power system”, Chaos, Solitons and Fractals, vol. 31 p. 665–671,
  6. Radu-Emil Precup • Marius L. Tomescu, (2014),Stable fuzzy logic control of a general class of chaotic systems, Neural Comput & Applic, DOI 10.1007/s00521-014-1644-7
  7. Huaqing Li n, XiaofengLiao,ChuandongLi,ChaojieLi, (2011), Chaos control and synchronization via a novel chatter free sliding mode control strategy, Neurocomputing, vol. 74, p. 3212–3222
  8. Tao Yang, (Member IEEE), and Leon O. Chua, Fellow, (1997), Impulsive Stabilization for Control and Synchronization of Chaotic Systems: Theory and Application to Secure Communication, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I: FUNDAMENTAL THEORY AND APPLICATIONS, vol. 44, NO. 10,
  9. M.T. Yassen, (2006),Chaos control of chaotic dynamical systems using backstepping design, Chaos, Solitons and Fractals, vol. 27,p. 537–548
  10. S. BOCCALETTI, C. GREBOGI, Y.-C. LAI, H. MANCINI, D. MAZA, (2000),HE CONTROL OF CHAOS: THEORY AND APPLICATIONS, Physics Reports, vol. 329. P. 103-197
  11. LM. Pecora, TL. Carroll, (1990), “Synchronization in chaotic systems”, Physics Rev Letters, vol. 64, p.821-824,
  12. ET. Hunt, (1991), “Stabilizing high-period orbits in a chaotic system: The diode resonator”, Physics Rev Letters, vol.66, p.1953-1991,
  13. Brown R, (1998), “Approximating the Mapping between Systems Exhibiting Generalized Synchronization”, Physics Rev Letter, vol. 81, p.4835,
  14. JZ. Yang, G. Hu, JH. Xiao, (1998), “Chaos Synchronization in Coupled Chaotic Oscillators with Multiple Positive Lyapunov Exponents”, Physics Rev Letters, vol. 80, pp. 496,
  15. EM. Shahverdiev, (2004), “Synchronization in systems with multiple time delays”, Phys Rev E, vol. P. 7006-7202,
  16. Haque ME, Zhong LM, Rahman MF. (2003), A sensorless initial rotor position estimation scheme for a direct torque controlled interior permanent magnet synchronous motor drive. IEEETransPowerElectron; vol.18, p.1376–83.
  17. Li, Z., Park, J.B., Joo, Y.H., Zhang, B., Chen, G.: Bifurcations and chaos in a permanent-magnet synchronous motor. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl. 49, 383–387 (2002)
  18. Ge, X., Huang, J.: (2005) Chaos control of permanent magnet synchronous motor. In: Proc. of the Eighth International Conference on Electrical Machines and Systems, Nanjing, China, vol. 1, pp. 484–488
  19. Ren, H., Liu, D. (2006). Nonlinear feedback control of chaos in permanent magnet synchronous motor. IEEE Trans. Circuits Syst. II, Express Briefs 53, 45–50
  20. Ren, H., Liu, D., Li, J. (2003) Delay feedback control of chaos in permanent magnet synchronous motor. Proc. Chin. Soc. Electron. Eng. Conf. Vol. 23, on. 6, p. 175–178
  21. Harb, A.M.: Nonlinear chaos control in a permanent magnet reluctance machine. Chaos Solitons Fractals 19, 1217–1224 (2004)
  22. Wei, D., Luo, X., Wang, B., Fang, J. (2009), Robust adaptive dynamic surface control of chaos in permanent magnet synchronous motor. Phys. Lett. A 363, 71–77 (2007) Zribi, M., Oteafy, A., Smaoui, N.: Controlling chaos in the permanent magnet synchronous motor. Chaos Solitons Fractals 41(3), 1266–1276
  23. JANG, J.S.R. (1993). Anfis adaptive-network-based fuzzy inference system. Systems Man and Cybernetics, IEEE Transactions on, 23, 665–685
  24. WANG, Z., PALADE, V. & XU, Y. (2006). Neuro-fuzzy ensemble approach for microarray cancer gene expression data analysis. In Evolving Fuzzy Systems, 2006 International Symposium on, 241 –246.
Index Terms

Computer Science
Information Sciences

Keywords

Neural fuzzy chaotic permanent magnet motor synchronization