Skip to main content
Log in

Adaptive robust fuzzy control for a class of uncertain chaotic systems

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

In this paper, the output feedback control of uncertain chaotic systems is addressed via an adaptive robust fuzzy approach. Fuzzy logic systems are employed to approximate uncertain nonlinear functions in the chaotic systems. Because only partial information of the system’s states is needed to be known, an observer is given to estimate the unmeasured states. Compared with the existing results in the observer design, the prior knowledge on dynamic uncertainties is relaxed and a class of more general chaotic systems is considered as well as robustness to the approximation error is improved. It can be proven that the closed-loop system is stable in the sense that all the variables are bounded. Simulation example for the unified chaotic systems is given to verify the effectiveness of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Chen, G.R.: Controlling Chaos and Bifurcations in Engineering Systems. CRC Press, Boca Raton (1999)

    Google Scholar 

  2. Ge, S.S., Wang, C.: Adaptive control of uncertain Chua’s circuits. IEEE Trans. Circuits Syst. I: Fundam. Theory Appl. 47(9), 1397–1402 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  3. Ge, S.S., Wang, C.: Uncertain chaotic system control via adaptive neural design. Int. J. Bifurc. Chaos 12(5), 1097–1109 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  4. Wang, C., Ge, S.S.: Adaptive backstepping control of uncertain Lorenz system. Int. J. Bifurc. Chaos 11(4), 1115–1119 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  5. Jiang, Z.P.: Advanced feedback control of the chaotic Duffing equation. IEEE Trans. Circuits Syst. I: Fundam. Theory Appl. 49(2), 244–249 (2002)

    Article  Google Scholar 

  6. Hua, C.C., Guan, X.P.: Adaptive control for chaotic systems. Chaos Solitons Fractals 22(1), 55–60 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  7. Hua, C.C., Guan, X.P., Shi, P.: Adaptive feedback control for a class of chaotic systems. Chaos Solitons Fractals 23(3), 757–765 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  8. Chen, B., Liu, X.P., Tong, S.C.: Adaptive fuzzy approach to control unified chaotic systems. Chaos Solitons Fractals 34(4), 1180–1187 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  9. Hua, C.C., Guan, X.P., Li, X.L., Shi, P.: Adaptive observer-based control for a class of chaotic systems. Chaos Solitons Fractals 22(1), 103–110 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  10. Tong, S.C., Li, H.X.: Direct adaptive fuzzy output tracking control of nonlinear systems. Fuzzy Sets Syst. 128, 107–115 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  11. Tong, S.C., Li, H.X., Wang, W.: Observer-based adaptive fuzzy control for SISO nonlinear systems. Fuzzy Sets Syst. 148(3), 355–376 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  12. Wang, C.H., Lin, T.C., Lee, T.T., Liu, H.L.: Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems. IEEE Trans. Syst. Man Cybern. Part B 32, 583–597 (2002)

    Article  Google Scholar 

  13. Kung, C.C., Chen, T.H.: Observer-based indirect adaptive fuzzy sliding mode control with state variable filters for unknown nonlinear dynamical systems. Fuzzy Sets Syst. 155(2), 292–308 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  14. Wang, J., Qiao, G.D., Deng, B.: Observer-based robust adaptive variable universe fuzzy control for chaotic system. Chaos Solitons Fractals 23(3), 1013–1032 (2005)

    MATH  MathSciNet  Google Scholar 

  15. Boulkroune, A., Tadjine, M., M’Saad, M., Farza, M.: How to design a fuzzy adaptive controller based on observers for uncertain affine nonlinear systems. Fuzzy Sets Syst. 159(8), 926–948 (2008)

    Article  MathSciNet  Google Scholar 

  16. Wang, L.X.: Fuzzy systems are universal approximators. In: IEEE International Conference on Fuzzy Systems, San Diego, pp. 1163–1170 (1992)

  17. Li, T.S., Yang, Y.S., Hu, J.Q., Yang, L.J.: Robust adaptive fuzzy tracking control for a class of perturbed uncertain nonlinear systems with UVCGF. Int. J. Wavelets Multiresolut. Inf. Process. 5(1), 227–239 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  18. Li, T.S., Hong, B.G., Shi, G.Y.: DSC-backstepping based robust adaptive NN control for strict-feedback nonlinear systems via small gain theorem. Int. J. Syst. Control Commun. 1(1), 124–145 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yan-Jun Liu.

Additional information

This work was supported in part by the National Natural Science Foundation of China (60874056) and the Foundation of Educational Department of Liaoning Province (2008312).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, YJ., Zheng, YQ. Adaptive robust fuzzy control for a class of uncertain chaotic systems. Nonlinear Dyn 57, 431–439 (2009). https://doi.org/10.1007/s11071-008-9453-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-008-9453-0

Keywords

Navigation