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Volume 40 Issue 11
Nov.  2014
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Journal of Beijing University of Aeronautics and Astronautics  > 2014  >  40(11): 1595-1601.
Hou Delong, Chen Bin, Wang Qing, et al. Dynamic surface control for hypersonic vehicle based on invariant manifold[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(11): 1595-1601. doi: 10.13700/j.bh.1001-5965.2013.0673(in Chinese)
Citation: Hou Delong, Chen Bin, Wang Qing, et al. Dynamic surface control for hypersonic vehicle based on invariant manifold[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(11): 1595-1601. doi: 10.13700/j.bh.1001-5965.2013.0673(in Chinese)
shu

Dynamic surface control for hypersonic vehicle based on invariant manifold

doi: 10.13700/j.bh.1001-5965.2013.0673
  • 1.

    Science and Technology on Aircraft Control Laboratory, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • 2. Beijing Astronautics Systems Engineering Institute, Beijing 100076, China

  • 3. Science and Technology on Aircraft Control Laboratory, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • 4. School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 21 Nov 2013
  • Publish Date: 20 Nov 2014
    Abstract
  • An adaptive dynamic surface control scheme based on invariant manifold was proposed for the longitudinal motion control problem of hypersonic vehicle. With reasonable hypothesis, the longitudinal dynamic model was separated into flight-path angle loop and velocity loop. Flight-path angle loop was formatted into parametric-strict-feedback form. The unknown parameters of the system were estimated based on the method of invariant manifold. The proposed dynamic surface control scheme can guarantee the global uniform stable of the error of estimation and the global boundedness of the closed system. The decoupled relationship between estimator and controller made the parameter tuning more easily than the traditional adaptive dynamic surface method. Simulation results validate the prominent improvement in parameters estimation and the good performance of the closed system.

     

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