Transitional Control Architecture and Methodology for a Twin Rotor Tailsitter

Hybrid unmanned aircraft can significantly increase the potential of micro air vehicles, because they combine hovering capability with a wing for fast and efficient forward flight. However, these vehicles are very difficult to control, because their aerodynamics are hard to model and they are susceptible to wind gusts. This often leads to composite and complex controllers, with different modes for hover, transition and forward flight. In this paper, we propose incremental nonlinear dynamic inversion control for the attitude and position control. The result is a single, continuous controller, that is able to track the desired acceleration of the vehicle across the flight envelope. The proposed controller is implemented on the Cyclone hybrid UAV. Multiple outdoor experiments are performed, showing that unmodeled forces and moments are effectively compensated by the incremental control structure. Finally, we provide a comprehensive procedure for the implementation of the controller on other types of hybrid UAVs.

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“…for V ≥ 6 m/s (7) with G 22 = −G 21 and where r θ is defined such that its value is always on the interval [0,1]:…”

Section: Control Effectiveness Schedulingmentioning

confidence: 99%

“…Considering the challenge of velocity control, many papers deal separately with hover, transition, and forward flight [9,25,7,28]. Although this approach may produce good results on days without wind, it is not very flexible; for instance when a constant wind requires the vehicle to fly like a fixed wing in order to maintain its position.…”

Section: Introductionmentioning

confidence: 99%

Incremental Control and Guidance of Hybrid Aircraft Applied to a Tailsitter Unmanned Air Vehicle

Smeur

Bronz

Croon

2020

Journal of Guidance, Control, and Dynamics

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“…For practical reasons, classical linear controllers designed using PID techniques have been applied in the control of hybrid MAVs. [7][8][9][10][11] Although simple to tune without the knowledge of the controlled system, PID controllers have insufficient robustness properties against wind disturbances. Autopilot systems designed from optimal control theory, have been researched.…”

Section: Literature Reviewmentioning

confidence: 99%

Model-free control algorithms for micro air vehicles with transitioning flight capabilities

Barth

Condomines

Bronz

et al. 2020

International Journal of Micro Air Vehicles

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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.

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“…The rotary-wing aircraft can take off vertically but usually has limitations in the forward flight, such as low speed and poor cruising ability (see Zhu et al (2017), Zhao et al (2015) and Wang et al (2018) to mention a few). Then, tail-sitter aerial vehicles, presented in Wang et al (2015), Stone (2008), Swarnkar et al (2018), Zhang et al (2018), and Forshaw et al (2014), have been developed to overcome their disadvantages: they can vertically take off and hover as rotary-wing aircrafts and cruise at high flight speeds as fixed-wing aircrafts.…”

Section: Introductionmentioning

confidence: 99%

Adaptive attitude controller design for tail-sitter unmanned aerial vehicles

Liu

Zhang³

et al. 2020

Journal of Vibration and Control

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Tail-sitter unmanned aerial vehicles have two flight modes: they can fly long distances at high cruising speeds as fixed-wing aircrafts; or hover, take off, and land vertically as rotary-wing aircrafts. The tail-sitter dynamics involves serious nonlinearities and high uncertainties, especially in the two flight mode transitions. In this article, an adaptive control approach is proposed for a class of tail-sitter unmanned aerial vehicles to achieve the robustness properties. The control torque allocation problem is addressed based on the dynamic pressure in the transition flight. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters in different flight modes. It is proven that the attitude tracking errors can converge into a given neighborhood of the origin in finite time. Simulation results are presented to show the advantages of the proposed adaptive control method.

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Transitional Control Architecture and Methodology for a Twin Rotor Tailsitter

Cited by 21 publications

References 16 publications

Incremental Control and Guidance of Hybrid Aircraft Applied to a Tailsitter Unmanned Air Vehicle

Incremental Control and Guidance of Hybrid Aircraft Applied to a Tailsitter Unmanned Air Vehicle

Model-free control algorithms for micro air vehicles with transitioning flight capabilities

Adaptive attitude controller design for tail-sitter unmanned aerial vehicles

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