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Controlling uncertain Genesio–Tesi chaotic system using adaptive dynamic surface and nonlinear feedback

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  • Gao, Shigen
  • Wang, Yubing
  • Dong, Hairong
  • Ning, Bin
  • Wang, Hongwei

Abstract

An adaptive dynamic surface control method using nonlinear feedback is proposed for controlling the uncertain Genesio-Tesi chaotic system. The feature of the nonlinear feedback technique lies in that the feedback gains self-adjust under different amplitudes of system states. Based on the dynamic surface control technique, the complexity explosion problem existing in the backstepping-based chaotic controllers is circumvented. Moreover, the closed-loop stability is guaranteed with rigorous mathematical proof using Lyapunov stability theorem. Comparative results are given to verify the effectiveness and advantage of the proposed method with comparison to the existing linear feedback control.

Suggested Citation

  • Gao, Shigen & Wang, Yubing & Dong, Hairong & Ning, Bin & Wang, Hongwei, 2017. "Controlling uncertain Genesio–Tesi chaotic system using adaptive dynamic surface and nonlinear feedback," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 180-188.
    • Handle: RePEc:eee:chsofr:v:105:y:2017:i:c:p:180-188
    DOI: 10.1016/j.chaos.2017.10.030
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    References listed on IDEAS

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    1. Park, Ju H., 2007. "Adaptive modified projective synchronization of a unified chaotic system with an uncertain parameter," Chaos, Solitons & Fractals, Elsevier, vol. 34(5), pages 1552-1559.
    2. Park, Ju H., 2006. "Synchronization of Genesio chaotic system via backstepping approach," Chaos, Solitons & Fractals, Elsevier, vol. 27(5), pages 1369-1375.
    3. Park, Ju H., 2007. "Adaptive controller design for modified projective synchronization of Genesio–Tesi chaotic system with uncertain parameters," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1154-1159.
    4. Messadi, M. & Mellit, A., 2017. "Control of chaos in an induction motor system with LMI predictive control and experimental circuit validation," Chaos, Solitons & Fractals, Elsevier, vol. 97(C), pages 51-58.
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