Micro air vehicles with transitioning flight capabilities, or simply hybrid micro air vehicles, combine the beneficial features of fixed-wing configurations, in terms of endurance, with vertical takeoff and landing capabilities of rotorcrafts to perform five different flight phases during typical missions, such as vertical takeoff, transitioning flight, forward flight, hovering and vertical landing. This promising micro air vehicle class has a wider flight envelope than conventional micro air vehicles, which implies new challenges for both control community and aerodynamic designers. One of the major challenges of hybrid micro air vehicles is the fast variation of aerodynamic forces and moments during the transition flight phase which is difficult to model accurately. To overcome this problem, we propose a flight control architecture that estimates and counteracts in real-time these fast dynamics with an intelligent feedback controller. The proposed flight controller is designed to stabilize the hybrid micro air vehicle attitude as well as its velocity and position during all flight phases. By using model-free control algorithms, the proposed flight control architecture bypasses the need for a precise hybrid micro air vehicle model that is costly and time consuming to obtain. A comprehensive set of flight simulations covering the entire flight envelope of tailsitter micro air vehicles is presented. Finally, real-world flight tests were conducted to compare the model-free control performance to that of the Incremental Nonlinear Dynamic Inversion controller, which has been applied to a variety of aircraft providing effective flight performances.
Transitioning vehicles experience three different flight phases during typical missions. The hovering and forward flight phases have been researched widely, however the transition phase in between is more challenging and has been the subject of less research. One of the control approaches to handle the transition phase relies on model-based methods which require sophisticated wind-tunnel characterization. Accurate modeling of force and moments of a partially stalled wing and control surfaces is highly challenging and time consuming. In addition, these models usually require several flight measurements (such as angle of attack and low airspeed) that are difficult to obtain. As an alternative, some control approaches manage the transition phase without the need for sophisticated models. One example of such an approach is the Model Free Control (MFC). This paper compares the results obtained from both MFC and Linear Quadratic Regulator (LQR) applied to fixed-wing UAV with transitioning flight capability during hovering, transition and forward flight modes. Both of the controllers are designed for a transitioning vehicle called MAVion. The simulation results demonstrated that MFC increases the stability of the aircraft, especially in disturbed flight conditions.
This paper discusses the development of a control architecture for hybrid Unmanned Aerial Vehicles (UAVs) based on model-free control (MFC) algorithms. Hybrid UAVs combine the beneficial features of fixed-wing UAVs with Vertical TakeOff and Landing (VTOL) capabilities to perform five different flight phases during typical missions, such as vertical takeoff, transitioning flight, forward flight, hovering and vertical landing. Based on model-free control principles, a novel control architecture that handles the hybrid UAV dynamics at any flight phase is presented. This unified controller allows autonomous flights without discontinuities of switching for the entire flight envelope with position tracking, velocity control and attitude stabilization. Simulation results show that the proposed control architecture provides an effective control performance for the entire flight envelope and excellent disturbance rejections during the critical flight phases, such as transitioning and hovering flights in windy conditions.
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