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Adaptive Fixed-Time Sliding Mode Control for Uncertain Twin-Rotor System with Experimental Validation

Author

Listed:
  • Linwu Shen
  • Qiang Chen
  • Meiling Tao
  • Xiongxiong He

Abstract

This paper proposes an adaptive fixed-time control scheme for twin-rotor systems subject to the inertia uncertainties and external disturbances. First of all, a fixed-time sliding mode surface is constructed and the corresponding controller is developed such that the fixed-time uniform ultimate boundedness of the sliding variable and tracking error could be guaranteed simultaneously, and the setting time is independent of the initial values. The adaptive update laws are developed to estimate the upper bounds of the lumped uncertainties and external disturbances such that no prior knowledge on the system uncertainties and disturbances is required. Finally, a twin-rotor platform is constructed to verify the effectiveness of proposed scheme. Comparative results show better position tracking performance of the proposed control scheme.

Suggested Citation

  • Linwu Shen & Qiang Chen & Meiling Tao & Xiongxiong He, 2019. "Adaptive Fixed-Time Sliding Mode Control for Uncertain Twin-Rotor System with Experimental Validation," Complexity, Hindawi, vol. 2019, pages 1-11, October.
    • Handle: RePEc:hin:complx:6582405
    DOI: 10.1155/2019/6582405
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    References listed on IDEAS

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    1. Zhongtian Chen & Qiang Chen & Xiongxiong He & Mingxuan Sun, 2018. "Adaptive Finite-Time Command Filtered Fault-Tolerant Control for Uncertain Spacecraft with Prescribed Performance," Complexity, Hindawi, vol. 2018, pages 1-12, November.
    2. Fang, Liandi & Ma, Li & Ding, Shihong & Zhao, Dean, 2019. "Finite-time stabilization for a class of high-order stochastic nonlinear systems with an output constraint," Applied Mathematics and Computation, Elsevier, vol. 358(C), pages 63-79.
    3. Ruisheng Sun & Jing Na & Bin Zhu, 2018. "Robust approximation-free prescribed performance control for nonlinear systems and its application," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(3), pages 511-522, February.
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