Learning-based Adaptive Fault Tolerant Control for Hypersonic Flight Vehicles with Abrupt Actuator Faults and Finite Time Prescribed Tracking Performance

Author(s):  
Supeng Zhu ◽  
Tao Xu ◽  
Caisheng Wei ◽  
Zheng Wang
Author(s):  
Jing-guang Sun ◽  
Shen-Min Song ◽  
Peng-Li ◽  
Guan-qun Wu

In this paper, related researches and analyses are conducted for the tracking problem of the hypersonic vehicle subject to external disturbances, actuator faults, and input saturation. Firstly, to achieve automatic adjustment of control gains and deal with the impact of dynamic failures of system without requiring prior knowledge of the fault, a new modified fast nonsingular terminal sliding manifold is proposed, and a fast adaptive finite time fault-tolerant controller is provided combining the adaptive control method and terminal sliding mode. Then, a fast adaptive finite time anti-saturation fault-tolerant controller is presented to further solve the problem of input saturation, under which both of the velocity and altitude can track respective reference signal with the actuator input constraint. Finally, the closed-loop stability under the proposed two adaptive fault-tolerant control schemes is analyzed, and numerical simulations of longitudinal model of the hypersonic vehicle are demonstrated to further confirm the effectiveness of the proposed approach.


2021 ◽  
Author(s):  
Zehong Dong ◽  
Yinghui Li ◽  
Maolong Lv ◽  
Ju Park ◽  
Dingshan Sun

Abstract This article proposes a new fixed-time fuzzy adaptive fault-tolerant control methodology for the longitudinal dynamics of hypersonic flight vehicles (HFVs) in the presence of actuator faults, uncertain dynamics and external disturbances. In contrast with the conventional fixed-time control schemes that typically contain the fractional powers of errors in their designs, this work develops a low-complexity control structure in the sense of removing the dependence on the need of above-mentioned fractional power terms by means of prescribed performance control (PPC) method. Different from the most existing PPC approaches where the initial conditions of tracking errors are required to be known, the newly proposed prescribed performance function (PPF) can relax such restrictions through choosing properly small initial values of PPF. Fuzzy logic systems (FLSs) are employed to handle unknown dynamics and minimal learning parameter (MLP) technique is incorporated into the design for the purpose of alleviating computation burden. Closed-loop stability is rigorously proved via Lyapunov stability theory and simulation results are eventually given to validate the effectiveness of the proposed control strategy.


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