Transition maneuvers are inherent challenges for tail-sitters because of the widely varying flight speed and pitch attitude. This paper investigates the dynamic model, the transition corridors, and...

Tailsitter unmanned aerial vehicles are utilized extensively nowadays since they merge advantages of both fixed-wing unmanned aerial vehicles and rotary-wing unmanned aerial vehicles. However, their attitude control suffers from unknown nonlinearities and disturbances due to the wide flight envelope. To solve the problems, a robust attitude controller based on a newly designed flying-wing tailsitter is proposed in this paper. By employing the angular acceleration feedback to compensate unmodeled dynamics, the proportional incremental nonlinear dynamic inversion control law is first developed. The proportional incremental nonlinear dynamic inversion strengthens the conventional nominal gain incremental nonlinear dynamic inversion with a proportional term to reflect the change of the angular acceleration more directly. Therefore, the tailsitter has a quicker response and performs better in suppressing model uncertainties and external disturbances. Since the angular acceleration is difficult to measure in practice, an angular acceleration estimation method is then established to provide accurate signals for the proportional incremental nonlinear dynamic inversion. The signals are derived as complementary results of model prediction method and direct differential method. Theoretical analysis and systematic simulations are conducted to corroborate the effectiveness of the developed estimation method as well as the robustness of the proposed controller.

This paper presents the development and hovering control of a tailsitter unmanned aerial vehicle (UAV) that merges long endurance and vertical takeoff and landing (VTOL) abilities. The designed tailsitter contains one flying-wing with two motors and two elevons. Vehicle aerodynamics and a six-degrees-of-freedom (6-DOF) model are especially developed for the tailsitter. To achieve a good performance in outdoor stationary hovering and accurate vertical flying, the active disturbance rejection control (ADRC) for attitude controller is proposed. With signals from extended state observer (ESO) and tracking differentiator (TD), ADRC decouples the system model into a controllable chain of integrators. Based on the decoupled system dynamics, the motion of tailsitter can be easily handled by developed position controller. Experimental results are presented to corroborate the effectiveness of the controller in disturbance rejection.

The online identification of aerodynamic coefficients for fixed-wing aircraft is crucial for designing flightcontrol laws and diagnosing faults; however; this issue has not yet been sufficiently addressed. To this end, this paper presents a parameter-estimation algorithm for fixed-wing aircraft based on an improved dynamic regressor extension and mixing (DREM) method. This algorithm can accurately and efficiently determine the aerodynamic coefficients under conventional maneuvering operations that do not meet the persistent-excitation condition. Taking into account the presence of external disturbances, adaptive backstepping control laws and disturbance observers (DOs) are incorporated based on the outcomes of online parameter identification. This approach seeks to achieve precise reference tracking and effective estimation and suppression of disturbances. Simultaneously, the integration of the DO and DREM estimators synergistically enhances their impact, leading to further refinement. The stability of the system is rigorously ensured throughout the design process. Finally, two comparative simulations and a hardware-in-the-loop experiment were conducted using a small fixed-wing UAV model to validate the efficacy and real-time performance of the proposed algorithm.