Ewoud Jan Jacob Smeur

This paper develops a guidance control law based on a parametric guiding vector field (GVF) and integrates it with a state-of-the-art acceleration and attitude control architecture for tailsitters. The resulting framework enables a direct comparison between traditional trajectory-tracking guidance and GVF-based path-following guidance using a realistic tailsitter model operating under windy conditions. Through extensive simulations, it is shown that for agile flight scenarios with wind and small initial position error, both guidance strategies achieve comparable tracking performance, indicating that the additional complexity introduced by the GVF formulation is not always justified. However, the GVF-based approach exhibits an advantage when initial deviation from the path is present, yielding smooth and well-behaved convergence toward the desired path. Two additional contributions support this evaluation. First, a modification of the parametric GVF is proposed that guarantees exponential stability of the tracking error dynamics for a single-integrator system. Second, the differential flatness transform of a tailsitter vehicle is extended to account for explicit knowledge of the wind velocity vector.

Though control algorithms for multirotor Unmanned Air Vehicle (UAV) are well understood, the configuration, parameter estimation, and tuning of flight control algorithms take quite some time and resources. In previous work, we have shown that it is possible to identify the control effectiveness and motor dynamics of a multirotor fast enough for it to recover to a stable hover after being thrown 4[Formula: see text]m in the air. In this paper, we extend this to include estimation of the position of the Inertial Measurement Unit (IMU) relative to the Center of Gravity (CoG), estimation of the IMU rotation, the thrust direction of all motors and the optimal combined thrust direction. In order to guarantee a correct IMU position estimation, two prior throw-and-catches of the vehicle with spin around different axes are required. For these throws, a height as low as 1[Formula: see text]m is sufficient. Quadrotor flight experimentation confirms the efficacy of the approach, and a simulation shows its applicability to fully-actuated crafts with multiple possible hover orientations.

In the aerospace control domain, Nonlinear Dynamic Inversion (NDI)-based control laws are widely spread. As a variation to Incremental Nonlinear Dynamic Inversion (INDI), the sensory Nonlinear Dynamic Inversion (sNDI) method was recently developed. Both methods rely on replacing model knowledge with sensor measurements. However, the methods differ in how the pseudo-controls are allocated: INDI allocates them incrementally, while sNDI allocates them globally, with corresponding advantages and disadvantages. While INDI requires a restoring mechanism in the control allocation due to path dependency issues in overactuated nonlinear systems, sNDI does not experience this problem. In addition to the comparison, the paper demonstrates that both methods lead to identical results if restoring is applied in the control allocation of INDI. Even though sNDI and INDI with restoring can lead to limit cycles for theoretical non-linear overactuated systems, the practical applicability of this approach to transition electrical vertical take-off and landing vehicles (eVTOL) is demonstrated in flight tests of the Variable Skew Quad Plane.

The inertia tensor is an important parameter in many engineering fields, but measuring it can be cumbersome and involve multiple experiments or accurate and expensive equipment. We propose a method to measure the moment of inertia tensor of a rigid body from a single spinning throw by attaching a small and inexpensive stand-alone measurement device consisting of a gyroscope, accelerometer, and a reaction wheel. The method includes a compensation for the increase of moment of inertia due to adding the measurement device to the body, and additionally obtains the location of the centre of gravity of the body as an intermediate result. Experiments performed with known rigid bodies show that the mean accuracy is around 2%. Monte Carlo simulations reveal invariance to direction of spin and positioning of the measurement device, but show some sensitivity to noise.

Tailsitter aircraft attract considerable interest due to their capabilities of both agile hover and high speed forward flight. However, traditional tailsitters that use aerodynamic control surfaces face the challenge of limited control effectiveness and associated actuator saturation during vertical flight and transitions. Conversely, tailsitters relying solely on tilting rotors have the drawback of insufficient roll control authority in forward flight. This paper proposes a tilt-rotor tailsitter aircraft with both elevons and tilting rotors as a promising solution. By implementing a cascaded weighted least squares (WLS) based incremental nonlinear dynamic inversion (INDI) controller, the drone successfully achieved autonomous waypoint tracking in outdoor experiments at a cruise airspeed of 16 m/s, including transitions between forward flight and hover without actuator saturation. Wind tunnel experiments confirm improved roll control compared to tilt-rotor-only configurations, while comparative outdoor flight tests highlight the vehicle's superior control over elevon-only designs during critical phases such as vertical descent and transitions. Finally, we also show that the tilt-rotors allow for an autonomous takeoff and landing with a unique pivoting capability that demonstrates stability and robustness under wind disturbances.