Achieving airbreathing hypersonic flight is an ongoing challenge with the potential to cut air travel time and provide cheaper access to space. Waveriders are potential candidates for achieving hypersonic cruise or acceleration flight within the atmosphere. Current research tends to focus on key issues like thermal loading, aero-elasticity and aerothermodynamics at hypersonic speeds. Design problems in each of these areas must be solved if a hypersonic waverider design is to be viable.

In this article, an on-line guidance strategy for terminal area energy management phase of a re-entry flight is proposed. In order to fulfil the objectives of this flight phase, the algorithm continuously performs long- and short-term on-line trajectory generation, also accounting for the most relevant vehicle and trajectory constraints. Long-term guidance computes a reference trajectory which minimizes the distance from the final target. Short-term guidance generates the control commands by computing a trajectory that minimizes the displacement from the reference one, thus compensating for the errors due to the environmental disturbances and to the uncertainties of the vehicle model. In the proposed guidance strategy, the main vehicle performance constraints are appropriately accounted for, thus guaranteeing adaptivity in the failure situations where the manoeuvring capabilities are reduced. The proposed guidance strategy has been developed in the framework of the unmanned space vehicle program of the Italian Aerospace Research Centre for the execution of Dropped Transonic Flight Test second mission. In this article, the algorithm performances and robustness to the vehicle initial state have been assessed through a preliminary Monte Carlo analysis. Furthermore, several simulations with bank angle and angle of attack limitations have shown the effectiveness of the algorithm in the presence of reduced manoeuvring capabilities.

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In this paper a Fault-Tolerant Control strategy against sensors failures for Hypersonic flight has been proposed. The novel approach is based on the robustness capabilities of Direct Model Following (DAMF) method and at the same time it uses sensors accuracy information to improve the adaptivity to sensors failures. DAMF is a Model Reference Control Strategy that asymptotically guarantees a null error between the output of the reference model and the one of the real plant, through a direct adaptation of control loop gains. The proposed algorithm modifies the Direct Adaptive Model Following method by adding a module, that varies the controller parameters having a direct influence on the updating rules of controller gains (i.e. on the adaptive capability of the controller) to obtain Fault Tolerance capabilities. A numerical analysis, carried out by using the flight dynamics model of FTB X vehicle, a flying test bed designed in the framework of Unmanned Space Vehicle programme of Italian Aerospace Research Centre, has demonstrated that the proposed fault-tolerant algorithm has good tracking performances and global closed loop stability in case of both single and multiple failures. Nomenclature x = plant system state vector y = plant system output vector y m = reference system output vector A m = reference system parameters B m = reference system parameters r = reference system input vector u = control law G 0 = adaptation gain matrix C 0 = adaptation gain matrix ν = adaptation gain matrix K 0 = feed-forward gain matrix P = matrix solution of the Lyapunov equation Q = positive definite weighting matrix A e = error matrix γ 1 = adaptation speed parameter γ 2 = adaptation speed parameter γ 3 = adaptation speed parameter R = matrix of the states feedback variables uncertainties R 0 = nominal value matrix of the states feedback variables uncertainties k = a scale factor α = angle of attack q = pitch rate σ = standard deviation of the sensor noise

In this article, an algorithm for three-dimensional path generation and tracking for unmanned air vehicles in the presence of no-fly zones is proposed. The algorithm is based on a local optimization procedure aimed to find the shortest path between the waypoints in compliance with all path constraints. Vehicle structural and envelope limitations are accounted for by simple geometric constraints such as minimum curvature radius and flight path angle limitations, while no-fly zones are defined as cylindrical objects with infinite altitude. The algorithm is simple and it has a limited computational burden, at most quadratic with the number of zones to avoid. This makes the algorithm very suitable for real-time applications even in case of a high number of forbidden zones. Algorithm effectiveness has been demonstrated by means of numerical simulations in scenarios including the presence of no-fly zones not known before flight (for instance, in the case of sudden changes of weather conditions and/or detection of new fixed obstacles).