Global Trajectory-tracking Control for a Tailsitter Flying Wing in Agile Uncoordinated Flight

Abstract

We propose a novel control law for accurate tracking of agile trajectories using a tailsitter flying wing micro unmanned aerial vehicle (UAV) that transitions between vertical take-off and landing (VTOL) and forward flight. Our global control formulation enables agile maneuvering throughout the flight envelope, including uncoordinated flight conditions with sideslip. We derive a differential flatness transform for the nonlinear tailsitter dynamics with a simplified aerodynamics model. Using this transform, the proposed controller incorporates accurate tracking of the position reference along with its temporal derivatives velocity, acceleration and jerk, as well as the yaw reference and yaw rate. The inclusion of jerk and yaw rate references through an angular velocity feedforward term increases tracking performance on agile trajectories with fast-changing accelerations. The control design is based on a simplified aerodynamics model that does not require extensive modeling of the aircraft dynamics. By applying incremental nonlinear dynamic inversion (INDI), the controller only depends on a local input-output relation to incrementally update control inputs, resulting in robustness against modeling inaccuracies. We achieve INDI with nonlinear dynamics inversion based on the derived differential flatness transform. The resulting control algorithm is extensively evaluated in flight tests, where it demonstrates accurate trajectory tracking and challenging agile maneuvers, such as uncoordinated sideways flight, aggressive transitions while turning, and differential thrust turning. Supplemental MaterialA video of the experiments can be found at https://youtu.be/tGQO-6DPT1M.

Aerobatic Trajectory Generation for a VTOL Fixed-Wing Aircraft Using Differential Flatness

“…In recent work on tailsitter flight control, we have shown how the vehicle attitude and angular velocity can be obtained based on the trajectory (15) and its derivatives up to yaw rate and jerk (i.e., the third derivative of position) [20]. In this section, we extend this derivation to obtain the full differential flatness transform, including an expression for the control inputs based on the trajectory derivatives up to yaw acceleration and snap.…”

“…Our recent work on trajectory-tracking flight control [20] presented a global model of the tailsitter flying wing dynamics based on the ϕ-theory parameterization introduced by [21]. In this section, we provide a brief overview of the dynamics model as a preliminary to the derivation of the corresponding flatness transform in Section III, which forms the basis of our trajectory generation algorithm.…”

“…Constraint (ii) is satisfied ∀k ∈ {0, 1} and, in practice, k can be set such that the obtained attitude trajectory is continuous. Finally, constraint (iii) is satisfied by equating ( 5) and (20) and solving for the collective thrust T = T 1 + T 2 and for the pitch rotation angle θ from the frame φ to the zero-lift reference frame.…”

“…Detailed descriptions of the experimental platform, shown in Fig. 8, and the trajectory-tracking flight control system are given in [28] and [20], respectively. A video of the experiments can be found at https://aera.mit.edu/projects/TailsitterAerobatics.…”

“…Secondly, we show differential flatness of the tailsitter flying wing dynamics model. We note that recent work on trajectory-tracking flight control for a tailsitter flying wing also leverages differential flatness of the global dynamics model [20]. However, this work does not include a method to obtain the control inputs as a function of the higher-order output derivatives, which is necessary for trajectory generation.…”