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Control of chaos in an induction motor system with LMI predictive control and experimental circuit validation

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  • Messadi, M.
  • Mellit, A.

Abstract

This paper concerns the control problems of an induction motor with chaotic behavior due to the defiance of indirect field oriented control applied with a proportional integral (PI) speed loop. The feedbacks predictive control is used to control this chaotic system owing to its simplicity of configuration and implementation. In general, the gain of the predictive control used in the literature is taken as a constant included in an interval, however, in this work, this gain is taken a matrix and Linear matrix inequality is using to calculate this gain. To highlight the efficiency and applicability of the proposed control scheme, simulations and experimental results are presented.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:97:y:2017:i:c:p:51-58
    DOI: 10.1016/j.chaos.2017.02.005
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    References listed on IDEAS

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    1. Tat-Bao-Thien Nguyen & Teh-Lu Liao & Jun-Juh Yan, 2014. "Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-11, February.
    2. Senouci, Abdelkader & Boukabou, Abdelkrim, 2014. "Predictive control and synchronization of chaotic and hyperchaotic systems based on a T–S fuzzy model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 105(C), pages 62-78.
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    Cited by:

    1. Singh, Piyush Pratap & Roy, Binoy Krishna, 2022. "Chaos and multistability behaviors in 4D dissipative cancer growth/decay model with unstable line of equilibria," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    2. J. Humberto Pérez-Cruz, 2018. "Stabilization and Synchronization of Uncertain Zhang System by Means of Robust Adaptive Control," Complexity, Hindawi, vol. 2018, pages 1-19, December.
    3. Anguiano-Gijón, Carlos Alberto & Muñoz-Vázquez, Aldo Jonathan & Sánchez-Torres, Juan Diego & Romero-Galván, Gerardo & Martínez-Reyes, Fernando, 2019. "On predefined-time synchronisation of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 172-178.
    4. Dutta, Maitreyee & Roy, Binoy Krishna, 2020. "A new fractional-order system displaying coexisting multiwing attractors; its synchronisation and circuit simulation," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    5. 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.
    6. Yu, Nanxiang & Zhu, Wei, 2021. "Event-triggered impulsive chaotic synchronization of fractional-order differential systems," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    7. Azarboni, H. Ramezannejad & Ansari, R. & Nazarinezhad, A., 2018. "Chaotic dynamics and stability of functionally graded material doubly curved shallow shells," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 14-25.

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