Pitot tube-free airspeed estimation methods exist for fixed-wing and multirotor configurations, but lack direct applicability to hybrid unmanned air vehicles due to their wide flight envelope and changing dynamics during transition. This work proposes a novel synthetic air data system for the Variable Skew Quad Plane (VSQP) hybrid vehicle to allow airspeed estimation from hover to high speed forward flight and provide pitot tube fault detection. An Extended Kalman Filter fuses Global Navigation Satellite System (GNSS) and inertial measurements using model-independent kinematics equations to estimate wind and airspeed without the use of the pitot tube. The filter is augmented by a simplified vehicle force model. Pitot tube fault detection is achieved with a simple thresholding operation on the pitot tube measurement and the airspeed estimation residual. Accurate airspeed estimation was validated with logged test flight data, achieving an overall 1.62 m/s root mean square error. Using the airspeed estimation, quick detection (0.16 s) of a real-life abrupt pitot tube fault was demonstrated. This new airspeed estimation method provides an innovative approach for increasing the fault tolerance of the VSQP and similar quad-plane vehicles.@en

Though control algorithms for multirotor Unmanned Air Vehicle (UAV) are well understood, the configuration, parameter estimation, and tuning of flight control algorithms takes 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 meters 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 meter is sufficient. Quadrotor flight experimentation confirms the efficacy of the approach, and a simulation shows its applicability to fullyactuated crafts with multiple possible hover orientations. @en

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.

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Fixed-wing aircraft fly longer, faster, and further than rotorcraft, but cannot take off or land vertically. Hybrid drones combine VTOL with a wing for forward flight, but the hovering system generally makes them less efficient than a pure fixed-wing. We propose an alternative, in which a rotorcraft is used to assist the fixed-wing UAV with the VTOL portions of the flight. This paper takes the first steps towards this alternative by developing and testing an overactuated rotorcraft that can autonomously dock onto a target at fixed-wing velocities. The control system uses Incremental Non-Linear Dynamic Inversion Control (INDI) to achieve linear accelerations with lateral and longitudinal motors, enabling robust horizontal control independent of attitude. A relative guidance algorithm for the docking approach path is presented, along with a vision sensing approach using ArUco markers and IR LEDs. Successful docking and separation were achieved in the wind tunnel at speeds of up to 15m/s. @en

This paper presents the design of an Incremental Nonlinear Dynamic Inversion (INDI) controller for the novel, patent pending (NL 2031701) platform Variable Skew Quad Plane (VSQP). Part of the identified challenges is the development of a model for the actuator effectiveness and lift especially as a function of skew, the newly added degree of freedom. The models and assumptions are verified through static and dynamic wind tunnel tests at the Open Jet Facility (OJF) of TU Delft. Transition tests have been successfully performed thanks to an automatic skew controller derived from the proposed models and aimed to maximize control authority.

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This paper presents a modular autopilot framework for Unmanned Aerial Vehicles (UAVs) that addresses the limitations of modern flight controllers. The framework utilizes separate and external subsystems for actuator control and the resolution of the Control Allocation problem. The actuator subsystem, implemented on a Teensy 4.0 microcontroller, incorporates an Incremental Dynamic Inversion Control (INDI) RPM controller, enabling direct control of motor RPM and facilitating the implementation of dynamic inversion-based control laws. The primary flight computer, a Cube Orange, coordinates the system, while an OrangePi 5 singleboard computer serves as a companion computer. Real flight results demonstrate the effectiveness of the framework, highlighting its potential for robust and efficient UAV control. @en

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.

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In vehicle control, control allocation is often used to abstract control variables from actuators, simplifying controller design and enhancing performance. Surveying available literature reveals that explicit solutions are restricted to strong assumptions on the actuators, or otherwise fail to exploit the capabilities of the actuator constellation. A remedy is to formulate hierarchical minimization problems that take into account the limits of the actuators at the expense of a longer computing time. In this paper, we compared the most common norms of the objective functions for linear or linearized plants, and show available numeric solver types. Such a comparison has not been found in the literature before and indicates that some combinations of linear and quadratic norms are not sufficiently researched. While the bulk of the review is restricted to control-affine plant models, some extensions to dynamic and nonlinear allocation problems are shown. For aerial vehicles, a trend toward linearized incremental control schemes is visible, which forms a compromise between real-time capabilities and the ability to resolve some nonlinearities common in these vehicles.@en

Utilizing wind hovering techniques of soaring birds can save energy expenditure and improve the flight endurance of micro air vehicles (MAVs). Here, we present a novel method for fully autonomous orographic soaring without a priori knowledge of the wind field. Specifically, we devise an Incremental Nonlinear Dynamic Inversion (INDI) controller with control allocation, adapting it for autonomous soaring. This allows for both soaring and the use of the throttle if necessary, without changing any gain or parameter during the flight. Furthermore, we propose a simulated-annealing-based optimization method to search for soaring positions. This enables for the first time an MAV to autonomously find a feasible soaring position while minimizing throttle usage and other control efforts. Autonomous orographic soaring was performed in the wind tunnel. The wind speed and incline of a ramp were changed during the soaring flight. The MAV was able to perform autonomous orographic soaring for flight times of up to 30 minutes. The mean throttle usage was only 0.25% for the entire soaring flight, whereas normal powered flight requires 38%. Also, it was shown that the MAV can find a new soaring spot when the wind field changes during the flight.

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We present a novel controller for fixed-wing UAVs that enables autonomous soaring in an orographic wind field, extending flight endurance. Our method identifies soaring regions and addresses position control challenges by introducing a target gradient line (TGL) on which the UAV achieves an equilibrium soaring position, where sink rate and updraft are balanced. Experimental testing validates the controller's effectiveness in maintaining autonomous soaring flight without using any thrust in a non-static wind field. We also demonstrate a single degree of control freedom in a soaring position through manipulation of the TGL.

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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.

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A type of UAV sharing the advantages of rotorcraft and fixed wing vehicles is the hybrid vehicle. Hybrid UAVs can take-off and land vertically and fly fast and efficient in forward flight due to the presence of a wing generating lift. However, combining the fixed wing and rotorcraft concept ends up in a multi-rotor with large dimensions when landed, and catching a lot of gust when hovering. Therefore, the oblique wing-quad plane drone has been developed which can rotate its quad arm and wing such that the wing can be aligned with the fuselage in hover. The wing can be rotated to fixed wing position during fast forward flight, stowing away one quad-arm. An INDI inner and outer loop controller has been implemented for this platform. Successful flight tests proved the feasibility of this controller and drone concept which is patent pending NL 2031701, Aeronautical Vehicle and Method of Transitioning between Flight Modes for an Aeronautical Vehicle, April 26th 2022, @en

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 manoeuvrability in a building. This paper proposes a novel combination of a quadrotor and a hybrid biplane capable of joint hover, joint forward flight, and mid-air disassembly 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. Secondly, to avoid communication the biplane leads the flight and the goal for the quadrotor is to help in producing thrust and increasing 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 intentional 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 for disturbance rejection has the lowest roll angle error and requires the smallest input command. The in-flight release is successfully tested in joint hover up to a forward pitch angle of -18 [deg]. @en

Applications of Unmanned Aerial Vehicles (UAVs) are often limited by flight endurance. To address the limitation of endurance, we propose a regenerative soaring method in this paper. The atmospheric energy from updrafts generated by obstacles such as hills and ships can be harvested by UAVs using a regenerative electric drivetrain. With fixed-wing aircraft, the vehicle can hover with specific wind conditions, and the battery can be recharged in the air while wind hovering. In order to research the feasibility of this regenerative soaring method, we present a model to estimate hovering locations and the amount of extractable power using the proposed method. The resulting modular regeneration simulation tool can efficiently determine the possible hovering locations and provide an estimate of the power regeneration potential for each hovering location, given the UAVs aerodynamic characteristics and wind-field conditions. Furthermore, a working regenerative drivetrain test setup was constructed and characterized that showcased promising conversion efficiencies and can be incorporated into existing UAVs easily.

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In the last few decades, the UAV research has been focusing on hybrid vehicles with Vertical Takeoff and Landing (VTOL) capabilities. Opposed to copters, hybrid vehicles are highly influenced by wind disturbances. This paper presents a novel quad-plane design that uses four dual-axis tilting rotors to enhance the wind rejection capability of a conventional quad-plane vehicle. After the non-linear mathematical model derivation and the actuator identification, the performance of the vehicle is addressed and compared to a conventional quad-plane in simulation, showing a factor 3.4 improvement in linear acceleration reaction time and a reduction of the gust induced displacement of 80%. Free-flight wind tunnel experiments confirmed the simulation outcome and extended the vehicle wind rejection capabilities behavior also to the lateral gust scenario.

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Many Unmanned Air Vehicle (UAV) applications require vertical take-off and landing and very long-range capabilities. Fixed-wing aircraft need long runways to land, and electric energy is still a bottleneck for helicopters, which are not range efficient. In this paper, we introduce the NederDrone, a hybrid lift, hybrid energy hydrogen-powered UAV that can perform vertical take-off and landings using its 12 propellers while flying efficiently in forward flight thanks to its fixed wings. The energy is supplied from a combination of hydrogen-driven Polymer Electrolyte Membrane fuel-cells for endurance and lithium batteries for high-power situations. The hydrogen is stored in a pressurized cylinder around which the UAV is optimized. This work analyses the selection of the concept, the implemented safety elements, the electronics and flight control and shows flight data including a 3h38 flight at sea while starting and landing from a small moving ship.

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Rotorcraft, fixed wing and hybrid Unmanned Air Vehicles (UAV) each have applications in which they excel. Traditionally, dedicated autopilot control code is written to accommodate flight of each UAV type. This causes fragmentation of control code and may lead to performance differences or errors. In this paper, we propose to use the same INDI controller for rotorcraft, fixed wing and hybrid UAVs, with only parametric differences in control effective matrix definitions and roll, pitch and airspeed limits. The controller is based on earlier work, but relevant derivations are included in this paper. Successful test flights, performed with a Bebop2 quadrotor, a Disco fixed wing, and a Nederdrone tailsitter hybrid demonstrate the feasibility of this approach. @en

Applications of Unmanned Aerial Vehicles (UAVs) are often limited by flight endurance. To address the limitation of endurance, we propose a regenerative soaring method in this paper. The atmospheric energy from updraft generated by obstacles such as hills and ships can be harvested by UAVs using a regenerative electric drivetrain. With fixed-wing aircraft, the vehicle can hover with specific wind condition, and the battery can be recharged in the air while wind hovering. In order to research the feasibility of this regenerative soaring method, we present a model to estimate hovering locations and the amount of extractable power using the proposed method. The resulting modular regeneration simulation tool can efficiently determine the possible hovering locations and provide an estimate of the power regeneration potential for each hovering location, given the UAVs aerodynamic characteristics and wind-field conditions. @en

Increasing endurance is a major challenge for battery-powered aerial vehicles. A method is presented which makes use of an updraft around obstacles to decrease the power consumption of a fixed-wing unmanned aerial vehicle. A soaring flight controller has been developed that can autonomously soar while the unmanned aerial vehicle keeps its relative position to that of a moving object. Multiple simulations have been performed to analyse the limitations of the soaring controller under different conditions. The effect of a change in wind velocity and updraft has been analysed. The simulations showed that an increase in updraft decreases the energy consumption of the flight controller. An increase in wind velocity results in a higher updraft requirement, while a decrease in the wind velocity requires less updraft. The simulations achieved sustained flight at 0% throttle. The controller has been validated experimentally using the updraft generated by a moving ship. The practical, autonomous tests reduced the average throttle down to 4.5% in front of a ship. The method presented in this study achieved successful hovering flight using an energy control module for longitudinal positioning.

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Flight endurance is still a bottleneck for many types of unmanned air vehicle (UAV) applications. While battery technology improves over the years, for flights that last an entire day, batteries are still insufficient. Hydrogen-powered fuel cells offer an interesting alternative but pose stringent requirements on the platform. The required cruise power must be sufficiently low and flying with a pressurized tank poses new safety and shape constraints. This paper proposes a hybrid transitioning UAV that is optimized towards carrying a hydrogen tank and fuel cell. Hover is achieved using 12 redundant propellers connected to a dual Controller Area Network (CAN) bus and dual power supply. Forward flight is achieved using a tandem wing configuration. The tandem wing not only minimizes the required wingspan to minimize perturbations from gusts during hover, but it also handles the very large pitch inertia of the inline pressure tank and fuel cell very well. During forward flight, 8 of the 12 propellers are folded while the tip propellers counteract the tip vortexes. The propulsion is tested on a force balance and the selected fuel cell is tested in the lab. Finally, a prototype is built and tested in-flight using battery power. Stable hover, good transitioning properties, and stable forward flight are demonstrated. @en