Adaptive neural control of a hypersonic vehicle in discrete time

Bin Xu, Danwei Wang, Han Wang, Senqiang Zhu

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

The article investigates the discretetime 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.

Original languageEnglish
Pages (from-to)219-231
Number of pages13
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Volume73
Issue number1-4
DOIs
StatePublished - Jan 2014

Keywords

  • Back-stepping
  • Hypersonic vehicle
  • Neural network

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