Deep Reinforcement Learning-Based Backstepping Control of Air-Breathing Hypersonic Vehicles with Actuator Constraints

Author(s):  
Guan Wang ◽  
Hao An ◽  
Ziyi Guo ◽  
Changli Yu ◽  
Hongwei Xia ◽  
...  
Author(s):  
H An ◽  
H Xia ◽  
C Wang

This paper designs a finite-time output tracking controller for air-breathing hypersonic vehicles (AHVs) subjected to disturbances and actuator constraints. After proper derivations, the original model is divided into two independent subsystems undergoing mismatched lumped disturbance. A finite-time disturbance observer (FTDO) is employed to estimate the lumped disturbance, while an auxiliary system combined with a command pre-filter is designed to analyze the effect of input saturation caused by the restrained actuators. Based on the FTDO and the auxiliary system, a novel integral sliding surface is constructed and then a chattering-free nonsingular controller is developed to realize finite-time output tracking in spite of mismatched lumped disturbance and input saturation, which is its major merit compared with other existing AHV controllers. A simulation study is carried out to verify the proposed control scheme.


Author(s):  
Tian Yan ◽  
Yuanli Cai ◽  
Bin Xu

AbstractThe rapid development of hypersonic vehicles has motivated the related research dramatically while the evasion of the hypersonic vehicles becomes one of the challenging issues. Different from the work based on the premise that the pursuers’ information is fully known, in this paper the evasion guidance for air-breathing hypersonic vehicles (AHVs) against unknown pursuer dynamics is studied. The gradient descent is employed for parameter estimation of the unknown dynamics of the pursuer. The energy-optimized evasion guidance algorithm is further developed by taking the acceleration constraint and energy optimization into consideration. Under the proposed algorithm, the system can deal with the unknown pursuer dynamics effectively and provide more practical guidance for the evasion process. The simulation results show that the proposed method can enable the AHV to achieve successful evasion.


Author(s):  
Chao Han ◽  
Zhen Liu ◽  
Jianqiang Yi

In this paper, a novel adaptive finite-time control of air-breathing hypersonic vehicles is proposed. Based on the immersion and invariance theory, an adaptive finite-time control method for general second-order systems is first derived, using nonsingular terminal sliding mode scheme. Then the method is applied to the control system design of a flexible air-breathing vehicle model, whose dynamics can be decoupled into first-order and second-order subsystems by time-scale separation principle. The main features of this hypersonic vehicle control system lie in the design flexibility of the parameter adaptive laws and the rapid convergence to the equilibrium point. Finally, simulations are conducted, which demonstrate that the control system has the features of fast and accurate tracking to command trajectories and strong robustness to parametric and non-parametric uncertainties.


2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Xingge Li ◽  
Gang Li

This article investigates a novel fuzzy-approximation-based nonaffine control strategy for a flexible air-breathing hypersonic vehicle (FHV). Firstly, the nonaffine models are decomposed into an altitude subsystem and a velocity subsystem, and the nonaffine dynamics of the subsystems are processed by using low-pass filters. For the unknown functions and uncertainties in each subsystem, fuzzy approximators are used to approximate the total uncertainties, and norm estimation approach is introduced to reduce the computational complexity of the algorithm. Aiming at the saturation problem of actuator, a saturation auxiliary system is designed to transform the original control problem with input constraints into a new control problem without input constraints. Finally, the superiority of the proposed method is verified by simulation.


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