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Adaptive Neural Control of a Hypersonic Vehicle in Discrete Time

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Abstract

The article investigates the discrete-time controller for the longitudinal dynamics of the hypersonic flight vehicle with throttle setting constraint. Based on functional decomposition, the dynamics can be decomposed into the altitude subsystem and the velocity subsystem. Furthermore, the discrete model could be derived using the Euler expansion. For the velocity subsystem, the controller is proposed by estimating the system uncertainty and unknown control gain separately with neural networks. The auxiliary error signal is designed to compensate the effect of throttle setting constraint. For the altitude subsystem, the desired control input is approximated by neural network while the error feedback is synthesized for the design. The singularity problem is avoided. Stability analysis proves that the errors of all the signals in the system are uniformly ultimately bounded. Simulation results show the effectiveness of the proposed controller.

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Authors and Affiliations

  1. School of Automation, Northwestern Polytechnical University, Xi’an, China

    Bin Xu

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Danwei Wang, Han Wang & Senqiang Zhu

Authors
  1. Bin Xu
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  2. Danwei Wang
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  3. Han Wang
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  4. Senqiang Zhu
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Correspondence to Bin Xu.

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Xu, B., Wang, D., Wang, H. et al. Adaptive Neural Control of a Hypersonic Vehicle in Discrete Time. J Intell Robot Syst 73, 219–231 (2014). https://doi.org/10.1007/s10846-013-9956-x

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  • DOI: https://doi.org/10.1007/s10846-013-9956-x

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