The purpose of this paper is to establish a transition strategy for tilt-rotor vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) based on an optimal design method. Firstly, The flyable transition corridor was calculated based on both the UAV’s dynamic equations and its aerodynamic and dynamic characteristics. The dynamic equations of the UAV were organized into state equation forms. The initial and final value constraints of the control and state variables in the transition process were recorded, as were the constraints of the transition process. The transition strategy design problem was transformed into an optimal control problem with constraints, while the Gauss pseudospectral method (GPM) was employed to transform and solve the problem. In addition, performance indicators were designed based on the transition quality requirements for transition time, attitude stability, and control continuity. Sensitivity was analyzed according to different index terms with different dimensions and effects. Finally, the rationality of the transition strategy designed in this paper was verified according to different simulation scenarios.

This paper proposes an adaptive fault-tolerant control strategy for a hybrid vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties. With the proposed adaptive control schemes, both actuator faults and model uncertainties can be accommodated without the knowledge of fault information and uncertainty bounds. The proposed control scheme is constructed with two separate control modules. The low-level control allocation module is used to distribute the virtual control signals among the available redundant actuators. The high-level control module is constructed with an adaptive sliding mode controller, which is employed to maintain the overall system tracking performance in both faulty and uncertain conditions. In the case of actuator faults and model uncertainties, the adaptive scheme will be triggered to generate more virtual control signals to compensate the virtual control error and maintain the desired system tracking performance. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios.