Tail-sitter Unmanned Aerial Vehicle Research Articles

Dynamic characteristics analysis and robust transition control of tail-sitter VTOL UAVs

The strong nonlinear dynamics of tail-sitter vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) have consistently constrained their applications. Particularly, the widely-varying flight speed and attitude during the transition flights pose substantial challenges for the controller design. In order to gain a clear understanding of the nonlinear transition flights, the long- and short- period dynamic characteristics of tail-sitter UAVs are investigated for the first time. The results reveal that the short-period mode exhibits either sluggish response or excessive overshoot in different transition stages, primarily due to the widely-varying damping ratio and natural angular frequency. Even worse, the long-period mode can diverge due to positive poles. To address these issues, a systematic controller is proposed. First, the transition trajectory is optimized and the optimal control inputs are employed in a feedforward manner to trim the nominal forces and moments. On this basis, a discrete-time linear quadratic regulation (LQR) controller with a predefined decay rate is developed to position the desired poles, and a novel angular acceleration estimation method is introduced to compensate for unmodeled dynamics. Simulations under different uncertainties indicate that the proposed control method performs better in both transition trajectory tracking and uncertainty suppression, compared to the PID and incremental nonlinear dynamic inversion (INDI) controllers.

Development of a tube-launched tail-sitter unmanned aerial vehicle

This paper describes the development and flight testing of a tail-sitter unmanned aerial vehicle (UAV) platform that has the potential to be tube-launched. Integrated with vertical take-off and landing (VTOL) capability, the platform can perform high-endurance loiter tasks along with low-speed and hovering flights, and land vertically in limited spaces. The current design utilizes a thrust-vectored counter-rotating coaxial propeller combined with a foldable conventional fixed-wing to accomplish both vertical and horizontal flights. A feedback control strategy capable of stabilizing and controlling the vehicle in both vertical and horizontal flight was designed and implemented on a custom-designed 1.7-gram autopilot. Several tests were conducted in hover and edgewise flight with aggressive pilot inputs to demonstrate the controllability of the aircraft even in the presence of moderate wind gusts. Additionally, transition flight tests were also performed, which demonstrated the vehicle’s capability of transitioning from vertical to fixed-wing horizontal flight using thrust-vectoring-based pitch control.

Safe Reinforcement Learning for Transition Control of Ducted-Fan UAVs

Ducted-fan tail-sitter unmanned aerial vehicles (UAVs) provide versatility and unique benefits, attracting significant attention in various applications. This study focuses on developing a safe reinforcement learning method for back-transition control between level flight mode and hover mode for ducted-fan tail-sitter UAVs. Our method enables transition control with a minimal altitude change and transition time while adhering to the velocity constraint. We employ the Trust Region Policy Optimization, Proximal Policy Optimization with Lagrangian, and Constrained Policy Optimization (CPO) algorithms for controller training, showcasing the superiority of the CPO algorithm and the necessity of the velocity constraint. The transition trajectory achieved using the CPO algorithm closely resembles the optimal trajectory obtained via the well-known GPOPS-II software with the SNOPT solver. Meanwhile, the CPO algorithm also exhibits strong robustness under unknown perturbations of UAV model parameters and wind disturbance.

A corridor-based flight mode transition strategy for agile ducted-fan tail-sitter UAV: Altitude-hold transition

As an attractive transition approach, the altitude-hold transition is a special type of super-maneuvering and the vertical/horizontal flight mode transition that an agile aircraft conducts at fixed altitude. However, it is still challenging to implement an autonomous control of the altitude-hold transition while the existing optimal transition planning methods cannot avoid an evident altitude change during the transition process. This paper proposes a corridor-based flight mode transition strategy and presents a successful flight demonstration of the altitude-hold transition on a small ducted-fan tail-sitter unmanned aerial vehicle. In the proposed corridor-based methodology, we model and analyze the transition corridor, concentrate on the dynamic characteristics of the altitude-hold transition, and emphasize that a valid transition trajectory should be governed by its transition corridor. The identified transition corridor reveals that for a given velocity trajectory, the solution for the corresponding trajectories of pitch angle and thrust is unique. Based on this, the transition trajectory generation problem is addressed simply on the velocity-acceleration plane. Furthermore, a proper flight control scheme is devised to track the generated transition trajectories. Finally, the effectiveness of the proposed method is verified through practical flight tests, in which the altitude change is less than 1.1 m during the entire transition course.

A Comprehensive Design and Experiment of a Biplane Quadrotor Tail-Sitter UAV

Tail-sitter unmanned aerial vehicles (UAVs) are promising vertical takeoff and landing (VTOL) UAV suitable for multi-missions but the road to the commercialization of tail-sitter UAVs is tortuous. This paper aims to provide a systematic design methodology and present the development process for a novel biplane quadrotor tail-sitter UAV platform named TW10 to accelerate commercialization of this type of UAV. All the design choices and trade-offs in aerodynamics, structure, avionics, and the control scheme are detailed. A simulation and real flight test results are demonstrated to prove the feasibility of our design methodology. TW10 can carry a 1 kg mission load to achieve more than 2.5 h of flight time. This work serves as a meaningful reference for the promotion of tail-sitter UAVs in practical industrial applications.

Transition control of a tail-sitter unmanned aerial vehicle with L1 neural network adaptive control

The main task of this work is to design a control system for a small tail-sitter Unmanned Aerial Vehicle (UAV) during the transition process. Although reasonable control performance can be obtained through a well-tuned single PID or cascade PID control architecture under nominal conditions, large or fast time-varying disturbances and a wide range of changes in the equilibrium point bring nonlinear characteristics to the transition control during the transition process, which leads to control precision degradation. Meanwhile, the PID controller’s tuning method relies on engineering experiences to a certain extent and the controller parameters need to be retuned under different working conditions, which limits the rapid deployment and preliminary validation. Based on the above issues, a novel control architecture of L1 neural network adaptive control associated with PID control is proposed to improve the compensation ability during the transition process and guarantee the security transition. The L1 neural network adaptive control is revised to solve the multi-input and multi-output problem of the tail-sitter UAV system in this study. Finally, the transition characteristics of the time setting difference between the desired transition speed and the desired transition pitch angle are analyzed.

Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

Vertical take-off and landing (VTOL) is a type of unmanned aerial vehicle (UAV) that is growing rapidly because its ability to take off and land anywhere in tight spaces. One type of VTOL UAV, the tail-sitter, has the best efficiency. However, besides the efficiency offered, some challenges must still be overcome, including the complexity of combining the ability to hover like a helicopter and fly horizontally like a fixed-wing aircraft. This research has two contributions: in the form of how the analytical model is generated and the tools used (specifically for the small VTOL quad tail-sitter UAV) and how to utilize off-the-shelf components for UAV empirical modeling. This research focuses on increasing the speed and accuracy of the UAV VTOL control design in fixed-wing mode. The first step is to carry out analysis and simulation. The model is analytically obtained using OpenVSP in longitudinal and lateral modes. The next step is to realize this analytical model for both the aircraft and the controls. The third step is to measure the flight characteristics of the aircraft. Based on the data recorded during flights, an empirical model is made using system identification technique. The final step is to vali-date the analytical model with the empirical model. The results show that the characteristics of the analytical mode fulfill the specified requirements and are close to the empirical model. Thus, it can be concluded that the analytical model can be implemented directly, and consequently, the VTOL UAV design and development process has been shortened.

Microphones as Airspeed Sensors for Unmanned Aerial Vehicles

This paper puts forward a novel design for an airspeed instrument aimed at small fixed-wing tail-sitter unmanned aerial vehicles. The working principle is to relate the power spectra of the wall-pressure fluctuations beneath the turbulent boundary layer present over the vehicle's body in flight to its airspeed. The instrument consists of two microphones; one flush-mounted on the vehicle's nose cone, which captures the pseudo-sound caused by the turbulent boundary layer, and a micro-controller that processes the signals and computes the airspeed. A feed-forward single-layer neural network is used to predict the airspeed based on the power spectra of the microphones' signals. The neural network is trained using data obtained from wind tunnel and flight experiments. Several neural networks were trained and validated using only flight data, with the best one achieving a mean approximation error of 0.043 m/s and having a standard deviation of 1.039 m/s. The angle of attack has a significant impact on the measurement, but if the angle of attack is known, the airspeed could still be successfully predicted for a wide range of angles of attack.

Robust Hierarchical Pinning Control for Nonlinear Heterogeneous Multiagent System With Uncertainties and Disturbances

This paper investigates the coordination control problem for a special nonlinear heterogeneous multi-agent system consisting of tail-sitter unmanned aerial vehicles and unmanned ground vehicles with uncertainties and disturbances. A robust hierarchical pinning control scheme is proposed for the heterogeneous multi-agent system to restrain the uncertainties and disturbances and achieve coordination scenarios. The heterogeneous multi-agent system can realize coordination tasks by selecting proper pinning nodes and estimating coupling strength. The robustness of the whole system is proven utilizing the Lyapunov stability theorem. The effectiveness of the robust hierarchical pining control method is validated by simulation scenarios.

The Hovering Stability of the Egretta Tail-Sitter VTOL UAV

Vertical takeoff and landing (VTOL) capability has extended the application of unmanned aerial vehicle (UAV) significantly. In this paper, simulation modeling and flight test were employed to investigate the hovering stability of a tail-sitter UAV named Egretta. The hovering stability simulation model was developed based on a simplified rigid body flight dynamic and the time-averaged propeller slipstream flow distribution. Meanwhile, a testing vehicle with PID controllers was built and tested to verify the hovering stability model. It was found that the Egretta UAV can achieve stable hovering in the roll, pitch, and yaw directions. The simulation model has demonstrated accuracy in predicting the hovering stability and dynamic responses with large perturbations in both trend and magnitude. Moreover, the simulation model can be extended to analyze the hovering stability of tail-sitter UAVs with different sizes. The simulation model will be very useful for initial stability sizing and PID optimization investigation.

Double Hybrid Tailsitter Unmanned Aerial Vehicle With Vertical Takeoff and Landing

We propose a new double-hybrid concept and architectural design of a tailsitter unmanned aerial vehicle with vertical takeoff and landing capability. Basically, it consists of a modified flying wing with a single combustion powertrain set and a multirotor with 2 powertrain sets with electric motors. With the electric propellers fixed at the leading wing edge, the tailsitter has two standard surfaces for elevation control and two vertical stabilizers that are used to give the necessary direction on vertical takeoff and landing. We have designed, built, and tested a prototype based on this new double-hybrid concept, which spends less energy on vertical taking off and landing and also on horizontal flight, thus maximizing flight endurance and travelled distance. We performed several experimental tests starting with the aircraft on the ground in vertical positioning. These tests include executing vertical takeoffs and landing, transitions from vertical to horizontal flight modes and transitions back (from horizontal to vertical), and hovering, which were carried out successfully. Transitions fourth and back from combustion to multirotor are inherent to some of those flight mode transitions, which have also been performed smoothly. We also performed tests (in bench) to estimate the maximum flight duration, which has demonstrated about 32 minutes of endurance. To this end, the proposed and currently built double-hybrid prototype has proven to be functional as an effective hybrid UAV system.

Modeling and control of a quadrotor tail-sitter unmanned aerial vehicles

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.

Transition characteristics for a small tail-sitter unmanned aerial vehicle

Research on the transition phase of tail-sitter Unmanned Aerial Vehicles (UAVs) is crucial for trajectory planning and performance analysis. This study focuses on the analysis of the transition characteristics and path of a small dual-rotor tail-sitter UAV, including static and dynamic computations. The system input time delay and actuator dynamics are specifically considered during the dynamic analysis, and these actual physical properties ensure that the computation results are reliable and reasonable. The UAV steady-state limit is obtained through static analysis, which is also adopted to verify the correctness of the dynamic results. In regard to the dynamic analysis, several typical transition approaches are computed based on different initial states and optimization objective functions, and the different computations are applicable under specific task conditions. The off-line dynamic results of the transition path and actuator output sequence could also be adopted as reference values for the transition process during real flight. A comparison of the static and dynamic results illustrates the necessity of combining these two methods for UAV transition characteristic analysis. Furthermore, the UAV conceptual parameters related to the transition path are also studied, and the obtained quantitative characteristics provide feedback for the UAV conceptual design.

A bio-inspired flight control strategy for a tail-sitter unmanned aerial vehicle

Wingbeat behavior and intermittent flight path are the two main characteristics of many birds. In this paper, to improve the efficiency of energy use and cruise range, a bio-inspired intermittent flight strategy with a whole flight envelope has applied to a tail-sitter aircraft. A total energy control system based transition control law has been proposed. The energy efficiency is investigated in terms of energy consumption per unit distance of different cruising modes, and the effectiveness and stability of proposed flight mode transition control law are verified by simulation. The mean mechanical power in flap-gliding flight is reduced compared with steady flight.

Robust proportional incremental nonlinear dynamic inversion control of a flying-wing tailsitter

Tailsitter unmanned aerial vehicles are utilized extensively nowadays since they merge advantages of both fixed-wing unmanned aerial vehicles and rotary-wing unmanned aerial vehicles. However, their attitude control suffers from unknown nonlinearities and disturbances due to the wide flight envelope. To solve the problems, a robust attitude controller based on a newly designed flying-wing tailsitter is proposed in this paper. By employing the angular acceleration feedback to compensate unmodeled dynamics, the proportional incremental nonlinear dynamic inversion control law is first developed. The proportional incremental nonlinear dynamic inversion strengthens the conventional nominal gain incremental nonlinear dynamic inversion with a proportional term to reflect the change of the angular acceleration more directly. Therefore, the tailsitter has a quicker response and performs better in suppressing model uncertainties and external disturbances. Since the angular acceleration is difficult to measure in practice, an angular acceleration estimation method is then established to provide accurate signals for the proportional incremental nonlinear dynamic inversion. The signals are derived as complementary results of model prediction method and direct differential method. Theoretical analysis and systematic simulations are conducted to corroborate the effectiveness of the developed estimation method as well as the robustness of the proposed controller.

Adaptive attitude controller design for tail-sitter unmanned aerial vehicles

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.

Transition Optimization for a VTOL Tail-Sitter UAV

This article focuses on the transition process optimization for a vertical takeoff and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV). For VTOL UAVs that can fly with either hover or cruise mode, transition refers to the intermediate phases between these two modes. This work develops a transition strategy with the trajectory optimization method. The strategy is a reference maneuver enabling the vehicle to perform transition efficiently by minimizing the cost of energy and maintaining a small change of altitude. The simplified three-degree-of-freedom longitudinal aerodynamic model is used as a dynamic constraint. The transition optimization problem is then modeled by nonlinear programming and solved by the collocation method to obtain the reference trajectory of the pitch angle and throttle offline. Simulations with the Gazebo simulator and outdoor flight experiments are carried out with the optimized forward (hover cruise) and backward (cruise hover) transition solutions. The simulation and experimental results show that the optimized transition strategy enables the vehicle to finish transition with less time and change of altitude compared with that by using traditional linear transition methods.

Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV.

This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2k full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum values. The time coefficient and air resistance were calculated using the computational fluid dynamics (CFD) method under different parameter combinations. The analysis of variance determined that the specific factors influencing the time coefficient and air resistance were the root chord, wingtip chord, wingspan, and sweep angle. By carrying out a central composite design (CCD) test, 25 sample points of the four particular factors were constructed. The time coefficient and air resistance were simulated under different structural parameter combinations using the CFD method. CFD simulation was verified by carrying out a wind tunnel test, and the results revealed that the aerodynamic coefficient error was less than 5%, while the air resistance error was less than 6%. The response surface methodology (RSM) for the time coefficient and air resistance was established using a genetic aggregation method. A multi-objective genetic algorithm (MOGA) was used to optimize the parameters with regard to the maximum time coefficient and minimum air resistance. The optimal structural parameters were wing root chord length at 315 mm, wingtip chord length at 182 mm, wingspan length at 1198 mm, and sweep angle at 16°. Compared with the original layout and size, the time coefficient of the new design of the tailsitter UAV improved by 19.5%, while the air resistance reduced by 34.78%. The results obtained by this study are significant for the design of tailsitter UAVs.

System Identification and Control for a Tail-Sitter Unmanned Aerial Vehicle in the Cruise Flight

This work presents the implementation of system identification and model predictive control for a tail-sitter unmanned aerial vehicle (UAV) in cruise flight. The mathematical model of longitudinal and lateral directions of the UAV has been derived in the state-space form for grey-box modeling. The least-square regression method is augmented with regulation and solved by applying the trust-region algorithm. Outdoor flight tests were conducted to acquire the data for system identification assisted by a signal generator module. The UAV dynamic was sufficiently excited in both longitudinal and lateral directions during the flight test. The flight data were applied to the grey box system identification, and the parameters were validated by fitting the reconstructed model to a set of flight data with a different excitation waveform. The flight controller with model predictive control was formed using the identified models for flight simulation. The results demonstrate that the system identification results are able to provide reference models for the model-based controller development of the novel-design tail-sitter UAV.

Position control of a tail-sitter UAV using successive linearization based model predictive control

A successive linearization based model predictive control (SLMPC) method is proposed to control a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hovering flight. The dynamic model of the vehicle is derived, including a low-fidelity aerodynamic model and a propulsion system model. The position controller is developed by a state–space prediction model augmented with estimated disturbance and feedback integration terms. The time-varying weight in the objective function is included and the velocity of vehicle is considered as reference to improve the performance. The system is first tested in a software-in-loop environment followed by the real-time indoor flight tests. The results demonstrate the vehicle can precisely follow a trajectory and stably hold position under unsteady wind disturbance