http://iet.metastore.ingenta.com
1887

Stochastic sampled-data controller for T–S fuzzy chaotic systems and its applications

Stochastic sampled-data controller for T–S fuzzy chaotic systems and its applications

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The present study mainly focuses on designing a stochastic sampled-data controller for chaotic Takagi–Sugeno (T–S) fuzzy systems. Distinct to the existing controller schemes, in this work, the random time delay is introduced into the proposed control scheme that ensures the exponential stabilisation of T–S fuzzy models. In addition, the input delays are assumed to be randomly time-varying, which copes with the traditional uncorrelated Bernoulli distributed sequences. Based on the proposed Lyapunov–Krasovskii functional and using new weighted integral inequalities, the stability and stabilisation conditions are derived and expressed in terms of linear matrix inequalities, which ensure the exponential stability of the states. Finally, in the simulation results, the chaotic nature of two dynamical systems are considered for validation of the derived conditions. From the simulation results, it is concluded that the proposed method can provide better stability performance and less conservative results.

References

    1. 1)
      • 1. Parker, T.S., Chua, L.O.: ‘Chaos: a tutorial for engineers’, Proc. IEEE, 1987, 75, (8), pp. 9821008.
    2. 2)
      • 2. Chiang, H.-D., Liu, C.-W., Varaiya, P.P., et al: ‘Chaos in a simple power system’, IEEE Trans. Power Syst., 1993, 8, (4), pp. 14071417.
    3. 3)
      • 3. Li, Z., Park, J.B., Joo, Y.H.: ‘Chaotifying continuous-time T–S fuzzy systems via discretization’, IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 2001, 48, (10), pp. 12371243.
    4. 4)
      • 4. Pehlivan, I., Uyaroğlu, Y.: ‘A new chaotic attractor from general Lorenz system family and its electronic experimental implementation’, Turkish J. Electr. Eng. Comput. Sci., 2010, 18, (2), pp. 171184.
    5. 5)
      • 5. Li, Z., Park, J.B., Joo, Y.H., et al: ‘Bifurcations and chaos in a permanent-magnet synchronous motor’, IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 2002, 49, (3), pp. 383387.
    6. 6)
      • 6. Chang, W., Park, J.B., Joo, Y.H., et al: ‘Static output-feedback fuzzy controller for Chen's chaotic system with uncertainties’, Inf. Sci., 2003, 151, pp. 227244.
    7. 7)
      • 7. Wu, Z.-G., Shi, P., Su, H., et al: ‘Sampled-data fuzzy control of chaotic systems based on a T–S fuzzy model’, IEEE Trans. Fuzzy Syst., 2014, 22, (1), pp. 153163.
    8. 8)
      • 8. Zhang, R., Zeng, D., Zhong, S., et al: ‘Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays’, Appl. Math. Comput., 2017, 310, pp. 5774.
    9. 9)
      • 9. Zhang, R., Zeng, D., Zhong, S.: ‘Novel master–slave synchronization criteria of chaotic Lur'e systems with time delays using sampled-data control’, J. Franklin Inst., 2017, 354, (12), pp. 49304954.
    10. 10)
      • 10. Zhang, R., Zeng, D., Zhong, S., et al: ‘New approach on designing stochastic sampled-data controller for exponential synchronization of chaotic Lur'e systems’, Nonlinear Anal., Hybrid Syst., 2018, 29, pp. 303321.
    11. 11)
      • 11. Ge, C., Shi, Y., Park, J.H., et al: ‘Robust H stabilization for T–S fuzzy systems with time-varying delays and memory sampled-data control’, Appl. Math. Comput., 2019, 346, pp. 500512.
    12. 12)
      • 12. Ge, C., Wang, B., Wei, X., et al: ‘Exponential synchronization of a class of neural networks with sampled-data control’, Appl. Math. Comput., 2017, 315, pp. 150161.
    13. 13)
      • 13. Ge, C., Wang, B., Park, J.H., et al: ‘Improved synchronization criteria of Lur'e systems under sampled-data control’, Nonlinear Dyn., 2018, 94, (4), pp. 28272839.
    14. 14)
      • 14. Ge, C., Park, J.H., Hua, C., et al: ‘Nonfragile consensus of multiagent systems based on memory sampled-data control’, IEEE Trans. Syst. Man Cybern., Syst., 2018, doi: 10.1109/TSMC.2018.2874305.
    15. 15)
      • 15. Zhang, R., Liu, X., Zeng, D., et al: ‘A novel approach to stability and stabilization of fuzzy sampled-data Markovian chaotic systems’, Fuzzy Sets Syst., 2018, 344, pp. 108128.
    16. 16)
      • 16. Liu, Y., Lee, S.-M.: ‘Stability and stabilization of Takagi–Sugeno fuzzy systems via sampled-data and state quantized controller’, IEEE Trans. Fuzzy Syst., 2016, 24, (3), pp. 635644.
    17. 17)
      • 17. Kim, H.J., Park, J.B., Joo, Y.H.: ‘Intelligent digital redesign for T–S fuzzy systems: sampled-data filter approach’, IET Control Theory Applic., 2018, 12, (9), pp. 13061317.
    18. 18)
      • 18. Kim, H.S., Park, J.B., Joo, Y.H.: ‘Sampled-data control of fuzzy systems based on the intelligent digital redesign method via an improved fuzzy Lyapunov functional approach’, IET Control Theory Applic., 2017, 12, (1), pp. 163173.
    19. 19)
      • 19. Kim, H.S., Park, J.B., Joo, Y.-H.: ‘A fuzzy Lyapunov–Krasovskii functional approach to sampled-data output-feedback stabilization of polynomial fuzzy systems’, IEEE Trans. Fuzzy Syst., 2018, 26, (1), pp. 366373.
    20. 20)
      • 20. Nilsson, J., Bernhardsson, B., Wittenmark, B.: ‘Stochastic analysis and control of real-time systems with random time delays’, Automatica, 1998, 34, (1), pp. 5764.
    21. 21)
      • 21. Al-Salami, I., Ding, S., Zhang, P.: ‘Fault detection system design for networked control system with stochastically varying transmission delays’, IFAC Proc. Vol., 2008, 41, (2), pp. 73757380.
    22. 22)
      • 22. Gao, H., Wu, J., Shi, P.: ‘Robust sampled-data H control with stochastic sampling’, Automatica, 2009, 45, (7), pp. 17291736.
    23. 23)
      • 23. Rakkiyappan, R., Chandrasekar, A., Lakshmanan, S.: ‘Stochastic sampled data robust stabilisation of T–S fuzzy neutral systems with randomly occurring uncertainties and time-varying delays’, Int. J. Syst. Sci., 2016, 47, (10), pp. 22472263.
    24. 24)
      • 24. Wen, S., Zeng, Z., Huang, T.: ‘Robust H output tracking control for fuzzy networked systems with stochastic sampling and multiplicative noise’, Nonlinear Dyn., 2012, 70, (2), pp. 10611077.
    25. 25)
      • 25. Dong, H., Wang, Z., Gao, H.: ‘Robust H filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts’, IEEE Trans. Signal Process., 2010, 58, (4), pp. 19571966.
    26. 26)
      • 26. Hu, J., Wang, Z., Gao, H., et al: ‘Robust sliding mode control for discrete stochastic systems with mixed time delays, randomly occurring uncertainties, and randomly occurring nonlinearities’, IEEE Trans. Ind. Electron., 2012, 59, (7), pp. 30083015.
    27. 27)
      • 27. Li, J., Wang, H.O., Niemann, D., et al: ‘Dynamic parallel distributed compensation for Takagi–Sugeno fuzzy systems: an LMI approach’, Inf. Sci., 2000, 123, (3-4), pp. 201221.
    28. 28)
      • 28. Miheev, Y.V., Sobolev, V.A., Fridman, E.M.: ‘Asymptotic analysis of digital control systems’, Automation and remote control, 1988, 49, (9), pp. 11751180.
    29. 29)
      • 29. Wang, J.-W., Li, H.-X., Wu, H.-N.: ‘Fuzzy guaranteed cost sampled-data control of nonlinear systems coupled with a scalar reaction–diffusion process’, Fuzzy Sets Syst., 2016, 302, pp. 121142.
    30. 30)
      • 30. Zaher, A.A.: ‘A nonlinear controller design for permanent magnet motors using a synchronization-based technique inspired from the Lorenz system’, Chaos: Interdiscip. J. Nonlinear Sci., 2008, 18, (1), pp. 013111.
    31. 31)
      • 31. Hou, Y.-Y.: ‘Controlling chaos in permanent magnet synchronous motor control system via fuzzy guaranteed cost controller’, Abstract Appl. Anal., 2012, 2012, doi: 10.1155/2012/650863.
    32. 32)
      • 32. Wang, Z.-P., Wu, H.-N.: ‘On fuzzy sampled-data control of chaotic systems via a time-dependent Lyapunov functional approach’, IEEE Trans. Cybern., 2015, 45, (4), pp. 819829.
    33. 33)
      • 33. Lam, H., Leung, F.F.: ‘Stabilization of chaotic systems using linear sampled-data controller’, Int. J. Bifurcation Chaos, 2007, 17, (6), pp. 20212031.
    34. 34)
      • 34. Wang, B., Wang, Y., Cao, H., et al: ‘LMI based fuzzy control of a wing doubled fractional-order chaos’, J. Control Sci. Eng., 2015, 2015, p. 29.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2018.5971
Loading

Related content

content/journals/10.1049/iet-cta.2018.5971
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address