Research on Non-stationary Control of Advanced Hypersonic Morphing Vehicles

Wei, Changzhu; Ju, Xiaozhe; He, Fenghua; Lu, Baogang

doi:10.2514/6.2017-2405

Cited by 5 publications

(4 citation statements)

References 3 publications

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“…Under the assumption of small angles, the attitude dynamic equation of the vehicle in the pitch channel can be presented as Equation (11), where the attitude coupling and external disturbances are not considered [31]. It is worth pointing out that the following model is only used to clearly realize the essential dynamics of the vehicles, but not to describe the accurate dynamics model.…”

Section: Mmfac Attitude Controller Designmentioning

confidence: 99%

A Modified Model-Free Adaptive Control Method for Large-Scale Morphing Unmanned Vehicles

Che¹,

Bai²

2023

Drones

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This paper investigates the attitude control problem for large-scale morphing unmanned vehicles. Considering the rapid time-varying and strong aerodynamic interference caused by large-scale morphing, a modified model-free control method utilizing only the system input and output is proposed. Firstly, a two-loop equivalent data model for the morphing unmanned vehicle is developed, which can better reflect the practical dynamics of morphing unmanned vehicles compared to the traditional compact form dynamic linearization data model. Based on the proposed data model, a modified model-free adaptive control (MMFAC) scheme is proposed, consisting of an external-loop and an inner-loop controller, so as to generate the required combined control torques. Additionally, in light of the aerodynamic uncertainties of the large-scale morphing unmanned vehicle, a rudder deflection actuator control scheme is designed by employing the model-free adaptive control approach. Finally, the boundedness of the closed-loop system and the convergence of tracking errors are guaranteed, based on the stability analysis. Additionally, numerical examples are presented to demonstrate the effectiveness and robustness of the proposed control scheme in the case of the effect of large-scale morphing.

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Section: Mmfac Attitude Controller Designmentioning

confidence: 99%

A Modified Model-Free Adaptive Control Method for Large-Scale Morphing Unmanned Vehicles

Che¹,

Bai²

2023

Drones

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“…The vehicles can perform a variety of missions under different flight conditions with excellent flight performance [2]. The research on this type of vehicle is mainly focused on structural design [3][4][5], trajectory planning [6,7], and attitude control [8][9][10], among which trajectory planning methods represent a very important research topic [3].…”

Section: Introductionmentioning

confidence: 99%

Predictor–Corrector Guidance for a Hypersonic Morphing Vehicle

Yao,

Xia

2023

Aerospace

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In an effort to address the problem of hypersonic morphing vehicles reaching the target while avoiding no-fly zones, an improved predictor–corrector guidance method is proposed. Firstly, the aircraft motion model and the constraint model are established. Then, the basic algorithm is given. The Q-learning method is used to design the attack angle and sweep angle scheme to ensure that the aircraft can fly over low-altitude zones. The B-spline curve is used to determine the locations of flight path points, and the bank angle scheme is designed using the predictor–corrector method, so that the aircraft can avoid high-altitude zones. Next, the Monte Carlo reinforcement learning (MCRL) method is used to improve the predictor–corrector method and a Deep Neural Network (DNN) is used to fit the reward function. The planning method in this paper realizes the use of a variable sweep angle, while the improved method further improves the performance of the trajectory, including the attainment of greater final speed and a smaller turning angle. The simulation results verify the effectiveness of the proposed algorithm.

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“…The flight control systems of morphing vehicles among the existing researches are mainly established on the assumption of static configuration [12][13][14][15]. Only in recent years, achieving stable flight control of morphing vehicles during shape transition phase has gained more and more attentions [16][17][18][19][20][21][22]. For instance, Yue applied Jacobian linearization approach to establish a linear parameter varying (LPV) model of a folding-wing aircraft [16], and proposed a gain self-scheduled robust controller to maintain stability during the wing folding process [17].…”

Section: Introductionmentioning

confidence: 99%

Data‐driven model‐free adaptive attitude control for morphing vehicles

Che

Wang

Luo

2022

IET Control Theory & Appl

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This paper investigates the attitude control problem of the morphing vehicle subject to great dynamics changes and disturbances during the morphing phase. An improved model‐free adaptive control (MFAC) method is proposed based on the compact format dynamic linearization technique. Firstly, a compact format data model and data‐driven control scheme are established based on the input/output (I/O) data of the controlled plant, independent of the complicated and time‐varying mathematical model of the morphing vehicle. Secondly, a series of historical output data errors in a moving time window are introduced to the control law, in which the length of the moving time window can be adjusted according to the system order of controlled plant. The convergence and stability of the improved control law are then proved theoretically, which guarantees the convergence of the tracking errors and the boundedness of the input and output data. Finally, numerical simulations are presented to evaluate the proposed approach, and comparisons are made with the conventional proportional‐derivative control method. Simulation results demonstrate that the improved method possesses better effectiveness and robustness in the presence of model changes and disturbances.

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Research on Non-stationary Control of Advanced Hypersonic Morphing Vehicles

Cited by 5 publications

References 3 publications

A Modified Model-Free Adaptive Control Method for Large-Scale Morphing Unmanned Vehicles

A Modified Model-Free Adaptive Control Method for Large-Scale Morphing Unmanned Vehicles

Predictor–Corrector Guidance for a Hypersonic Morphing Vehicle

Data‐driven model‐free adaptive attitude control for morphing vehicles

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