Robust Adaptive Control of Hypersonic Vehicle Considering Inlet Unstart

Fan Wang, Pengfei Fan, Yonghua Fan, Bin Xu, Jie Yan

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper, a model reference adaptive control (MRAC) augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle (AHV) during inlet unstart. With the development of hypersonic flight technology, hypersonic vehicles have been gradually moving to the stage of weaponization. During the maneuvers, changes of attitude, Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet. Inlet unstart causes significant changes in the aerodynamics of AHV, which may lead to deterioration of the tracking performance or instability of the control system. Therefore, we firstly establish the model of hypersonic vehicle considering inlet unstart, in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty. Then, an MRAC augmentation method of a linear controller is proposed and the radial basis function (RBF) neural network is used to schedule the adaptive parameters of MRAC. Furthermore, the Lyapunov function is constructed to prove the stability of the proposed method. Finally, numerical simulations show that compared with the linear control method, the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart, which provides favorable conditions for inlet restart, thus verifying the effectiveness of the augmentation method proposed in the paper.

Original languageEnglish
Pages (from-to)188-196
Number of pages9
JournalJournal of Systems Engineering and Electronics
Volume33
Issue number1
DOIs
StatePublished - 1 Feb 2022

Keywords

  • air-breathing hypersonic vehicle (AHV)
  • inlet unstart
  • model reference adaptive control augmentation (MRAC)
  • radial basis function (RBF) neural network

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