This paper proposes a flight risk analysis method that combines risk assessment and visual deduction to study the causes of flight accidents, specifically the loss of control caused by failure factors. The goal is to explore the impact of these failure factors on loss-of-control events and illustrate the risk evolution under different scenarios in a clear and intuitive manner. To achieve this, the paper develops a failure scenario tree to guide flight simulations under different loss-of-control scenarios. The next step involves developing a multi-parameters risk assessment method that can quantify flight risk at each time step of the flight simulation. This assessment method uses entropy weight and a grey correlation algorithm to assign variable weights to the different parameters. Finally, the paper presents the visual deduction of the risk evolution process under different loss-of-control scenarios using a risk tree that concisely represents the time-series risk assessment results and failure logical chains. Taking three common failure factors (actuator failure, engine failure, and wing icing) as cases, the paper designs 25 different loss-of-control scenarios to demonstrate the flight risk analysis method. By comparing the risk evolution process under different loss-of-control scenarios, the paper explores the impact of the failure factors on flight safety. The analysis results indicate that this method combines risk analysis from both individual and global perspectives, enabling effective analysis of risk evolution in loss-of-control events.@en

A new fixed-time fuzzy adaptive fault-tolerant control methodology is proposed 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 abovementioned 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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This paper investigates the problems of modeling and control of the morphing aircraft. Henceforth, a nonlinear dynamic model of a wing-sweep morphing aircraft is first established in this work. This model is suitable for larger envelopes by elaborating the variation of aerodynamic coefficients, air density, mass distribution at different altitudes, Mach numbers, and sweep angles. Considering the alterations in the dynamic characteristics of the morphing aircraft owing to the various flight conditions, we design the switching adaptive backstepping controllers for the altitude subsystem and velocity subsystem. The actuator dynamics have been explicitly included in the process of the controller design to alleviate the chattering problem caused by the switching. Furthermore, the closed-loop stability is rigorously proved via the Lyapunov stability theory and the technique of compact set. Comparative results from the simulations finally validate the effectiveness of the proposed scheme.

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