Robust adaptive control of hypersonic vehicle considering inlet unstart  

作　　者：WANG Fan FAN Pengfei FAN Yonghua XU Bin YAN Jie 

机构地区：[1]College of Astronautics,Northwestern Polytechnical University,Xi’an 710072,China [2]College of Automation,Northwestern Polytechnical University,Xi’an 710072,China

出　　处：《Journal of Systems Engineering and Electronics》2022年第1期188-196,共9页系统工程与电子技术（英文版）

基　　金：supported by the Foundation of Shanghai Aerospace Science and Technology(SAST2016077)。

摘　　要：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.

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

分 类 号：V249.1[航空宇航科学与技术—飞行器设计] V448[自动化与计算机技术—检测技术与自动化装置] TP273[自动化与计算机技术—控制科学与工程]