This study investigates how coordinated rotor tilt and elevon deflection shape the aerodynamic performance and maneuvering capability of a tilt-rotor tailsitter UAV, with particular emphasis on high-speed sharp turns where maximizing lift is essential for minimizing turning radius. Extensive wind tunnel experiments were conducted across a range of airspeeds, angles of attack, throttle settings, and actuator combinations to quantify axial force, lift, and pitching moment while capturing the effects of wing–propeller interaction. Pitching-moment trim tests were also performed by dynamically adjusting actuator input combinations to maintain pitch moment equilibrium. The results show that upward rotor tilt, when combined with downward elevon deflection, produces substantially higher lift while preserving pitch moment equilibrium within the tested positive-AoA forward flight envelope, outperforming either actuation used alone. By embedding the derived empirical models into an equilibrium-constrained sharp turn maneuver, the study further predicts a theoretical minimum turning radius of 8.01 m at 18 m/s under an extrapolated throttle command condition, corresponding to a 31.8% reduction compared to an equivalent fixed-rotor tailsitter with elevons, suggesting that synergistic thrust vectoring and control-surface deflection enable aggressive maneuvers without compromising pitch stability or forward speed.

It has recently been shown that all physical parameters of an Incremental Nonlinear Dynamic Inversion (INDI) controller can be estimated onboard a multirotor within half a second, which is fast enough to do the full identification during a throw in the air. However, a robust method to tune outer loop gains for this feedback-linearizing INDI controller depending on the model parameters is still missing. This work presents the design of a robust gain-scheduled controller for attitude control of quadrotor, using an INDI-based inner loop with online identification of its system parameters. A gainscheduled cascaded attitude controller with a feedforward filter is synthesized for a symmetric quadrotor using signalbased H_∞ closed-loop shaping. The resulting controller exhibits good stability margins, with nonlinear simulations confirming effective tracking performance under uncertainty. Experimental evaluation is also conducted through flight tests with full online parameter identification. Even though the identified parameters during these tests are far outside the defined uncertainty range, acceptable flight performance comparable to simulation results is maintained for actuator time constants below 40 ms.

The operation of heavy hybrid Unmanned Aerial Vehicles (UAVs) in populated areas demands robust Fault Tolerant Control (FTC) strategies to ensure safe landings following actuator failures. This paper presents the first successful reallife demonstration of stable relaxed hover on a large hybrid drone, the Variable Skew Quad Plane (VSQP), subject to the total loss of control authority in two opposing multirotor motors while in forward-flight mode. A modified Incremental Nonlinear Dynamic Inversion (INDI) controller is derived to regulate the vehicle's principal axis of rotation. The framework is extended to actively incorporate aerodynamic control surfaces (flaperons), which are shown to significantly improve the rejection of unmodelled aerodynamic and reaction moments. Furthermore, alongside a standard position controller, a novel pusher-motor guidance strategy is proposed and flight-tested. By exploiting the pusher motor the control-authority requirements on the primary stabilization actuators are reduced. The controller achieves fully autonomous tracking of a square trajectory. These results confirm the efficacy of INDI for executing relaxed hover on large quad-planes equipped with aerodynamic surfaces, and demonstrate the benefits of leveraging the full suite of hybrid UAV actuators.

This work introduces a novel analytical model for estimating the airspeed of fixed-wing Unmanned Aerial Vehicles (UAVs) using solely propeller power and rotational speed measurements. The model can be used to replace Pitot-tube-based airspeed sensors, or contribute to redundancy in airspeed estimation. It does not require knowledge of the vehicle’s dynamic model and is computationally lightweight. It leverages power and rotational speed feedback, which is readily available from modern Electronic Speed Controllers (ESCs), thereby enabling seamless integration with existing systems and off-the-shelf components. A systematic approach is followed to derive the model structure based on least squares optimization and regularization techniques on Blade Element Momentum (BEM) simulation, wind tunnel, and flight test datasets. The final model generalizes well achieving a normalized Root Mean Square Error (nRMSE) of 5 % on unseen flight data. The model coefficients can be identified either offline, using flight logs with airspeed measurements, or in-flight, using a lightweight identification method based only on Global Positioning System (GPS) velocity data. The resulting system provides a robust and computationally efficient solution for real-time airspeed estimation across diverse fixed-wing UAV platforms.

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.

Expanding the operational capabilities of Micro Air Vehicles (MAVs) hinges on control systems that manage highly nonlinear dynamics across broad flight envelopes. Incremental Nonlinear Dynamic Inversion (INDI) is popular for its simplicity and modest modeling needs, but its assumption of infinitely fast actuators and neglect of state-dependent effects limit performance when actuators have slow or heterogeneous dynamics or when aerodynamic effects are significant. Actuator Nonlinear Dynamic Inversion (ANDI) overcomes these limitations by explicitly incorporating state-dependent dynamics and finite actuator bandwidth into the control law, enabling improved tracking performance across diverse actuator configurations. This work implements the full ANDI stabilization controller on the Cyclone, a hybrid MAV tail-sitter, using cascaded complementary filtering for state estimation. Simulation and flight experiments validate the approach and assess whether this compensation yields practical performance gains, establishing ANDI as a viable, generic control solution for MAVs. Code is available at https://github.com/tudelft/paparazzi/tree/feat_stabilization_andi_controller.

Incremental Nonlinear Dynamic Inversion (INDI) has become a popular control strategy for unmanned aerial vehicles due to its disturbance rejection capabilities and minimal model reliance. However, its standard formulation neglects actuator dynamics, leading to undesired coupling in systems with heterogeneous actuator characteristics such as in the Variable Skew Quad Plane (VSQP). This paper analyzes the limitations of INDI in such scenarios and demonstrates how Actuator Nonlinear Dynamic Inversion (ANDI) solves them. The closed-loop transfer function analysis shows how ANDI eliminates cross-axis coupling by directly incorporating actuator dynamics into the control allocation process. Additionally, ANDI is compared to a modified INDI approach that employs lead-lag filters to homogenize actuator behavior. While this approach is effective in decoupling, it unnecessarily slows down system response and worsens saturation handling. Simulation and flight test results using the VSQP validate the theoretical findings, confirming that ANDI offers improved control accuracy on coupled axes without compromising performance on decoupled axes.

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 letter 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.

This paper presents a method to recover quadrotor Unmanned Air Vehicles (UAVs) from a throw, when no control parameters are known before the throw. We leverage the availability of high-frequency rotor speed feedback available in racing drone hardware and software to find control effectiveness values and fit a motor model using recursive least squares (RLS) estimation. Furthermore, we propose an excitation sequence that provides large actuation commands while guaranteeing to stay within gyroscope sensing limits. After 450ms of excitation, an Incremental Nonlinear Dynamic Inversion (INDI) attitude controller uses the 52 fitted parameters to arrest rotational motion and recover an upright attitude. Finally, a Nonlinear Dynamic Inversion (NDI) position controller drives the craft to a position setpoint. The proposed algorithm runs efficiently on microcontrollers found in common UAV flight controllers, and was shown to recover an agile quadrotor every time in live experiments with as low as 3.5m throw height, demonstrating robustness against initial rotations and noise. We also demonstrate control of randomized quadrotors in simulated throws, where the parameter fitting Root-Mean-Square (RMS) error is typically within 10% of the true value.

Hybrid Unmanned Aerial Vehicles UAV are vehicles capable of take-off and landing vertically like helicopters while maintaining the long-range efficiency of fixed-wing aircraft. Unfortunately, due to their wing area, these vehicles are sensitive to wind gusts when hovering. One way to increase the hovering wind-rejection capabilities of hybrid UAV is through the addition of extra actuators capable of directing the thrust of the rotors. Nevertheless, the ability to control UAVs with many actuators is strictly related to how well the Control Allocation problem is solved. Generally, to reduce the problem complexity, conventional (CA) methods make use of linearized control effectiveness in order to optimize the inputs that achieve a certain control objective. We show that this simplification can lead to oscillations if it is applied to thrust vectoring vehicles, with pronounced non-linear actuator effectiveness. When large control objectives are requested or actuators saturate, the linearized effectiveness based CA methods tend to compute a solution far away from the initial actuator state, invalidating the linearization. A potential solution could be to impose limits on the solution domain of the linearized CA algorithm. However, this solution only reduces the oscillations at the expense of a lag in the vehicle acceleration response. To overcome this limitation, we present a fully nonlinear CA method, which uses an Sequential Quadratic Programming (SQP) algorithm to solve the CA problem. The method is tested and implemented on a single board computer that computes the actuator solution in real time onboard a dual axis tilting rotor quad-plane. Flight test experiments confirm the problem of severe oscillations in the linearized effectiveness CA algorithms and show how the only algorithm able to optimally solve the CA problem is the presented Nonlinear method.

Unmanned Aerial Vehicles (UAVs) have the potential to perform many different missions, some of which may require a large aircraft for endurance and a small aircraft for maneuverability in wind gusts or cluttered environments such as buildings. This paper proposes a novel combination of a quadrotor and a hybrid biplane capable of joint hover, joint forward flight, and mid-Air separation followed by separate flight. We investigate cooperative control strategies during joint flight that do not require any communication between the quadcopter and the biplane. This means that the two aircraft have their own independent control strategy based on their own sensors. The biplane, which is the largest of the two with most control authority, leads the flight and the goal for the quadrotor is to help in producing thrust and increasing rotational stability. Three control strategies for the quadrotor are compared: A proportional angular rate damper, a proportional angular acceleration damper, and constant thrust without attitude control. Simulation and practical tests show that for desired attitude changes of the biplane, the quadrotor rate-and angular acceleration damper strategies lead to a small performance degradation. However, the angular rate damper strategy reduces the roll angle error in disturbance rejection experiments and requires the smallest input command. The in-flight release is successfully tested in joint hover up to a forward pitch angle of-18.