The main aim of this paper is to establish the relationship between the airfoil flutter with the flight dynamics of a generic hypersonic flight vehicle (HFV) and analyze the airfoil damage variation during the airfoil flutter. Based on the motion equations of the two degrees of freedom airfoil model and the longitudinal dynamics of the HFV, an airfoil dynamic model is established. By using a coupling equation, the relationship between airfoil flutter and the flight dynamics is estimated. According to the stress–strain ([Formula: see text]) model and the strain–fatigue damage ([Formula: see text]) model, the influence of the stress on the airfoil flutter damage is analyzed. The simulation results show that the flutter of the airfoil is closely related to the flight dynamics for the HFV and the airfoil flutter damage is closely related to the flutter amplitude of the airfoil.
The complex nonlinearities of hypersonic vehicles can lead to strong couplings between variables, which will bring great challenges to flight control. For this purpose, this paper proposes a novel coupling analysis method for the longitudinal dynamics of a hypersonic vehicle, based on which a coordination controller is designed to reduce the negative effects of the couplings. Initially, according to the coupling characteristics of the hypersonic vehicle, a novel coupling analysis method based on the dynamic equations is proposed to describe the dynamic coupling relationships between variables. Then, a coordination control scheme is designed by combining sliding mode control and the dynamic coupling matrix obtained. Subsequently, the asymptotic stability of the closed-loop system is proved by using Lyapunov theory, and the simulation results are given to verify the effectiveness of the proposed dynamic coupling matrix-based coordination control.
The trajectory tracking control problem of an omnidirectional mobile robot is studied in this article. The omnidirectional mobile robot is adsorbed by suction cups for aircraft skin inspection, which is a typical nonholonomic system. In the control design part, a novel adaptive neural network control scheme is presented in the presence of uncertainty and external disturbance. The adaptive neural network has the characteristics of weights online updating. The neural network is applied to estimate uncertainty online to obtain the desired tracking performance. The weights online updating algorithm contains a correction term, which is an improved algorithm to ensure robustness. On the basis of Lyapunov theory, the closed-loop system can converge to an arbitrarily small domain containing origin. This illustrates that the closed-loop system is globally asymptotically bounded stable. Excellent control performance can be obtained by selecting design parameters reasonably. A simulation example of tracking an eight-shape trajectory is given to verify the effectiveness of the proposed control scheme.
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