The miniature tailsitter is a unique aircraft with inherent advantages over typical unmanned aerial vehicles. With the capabilities of both hover and level flight, these small, portable systems can produce efficient maneuvers for enhanced surveillance and autonomy with little threat to surroundings and the system itself. Such vehicles are accompanied with control challenges due to the two different flight regimes. Problems with the conventional attitude representation arise in estimation and control as the system departs from level flight conditions. Furthermore, changing dynamics and limitations in modeling and sensing give rise to significant attitude control design challenges. Restrictions in computation also result from the limited size and weight capacity of the miniature airframe. In this research, the inherent control challenges discussed above are addressed with a computationally efficient adaptive quaternion control algorithm. A backstepping method for model cancellation and consistent tracking of reference model attitude dynamics is derived. This is used in conjunction with two different algorithms designed for the identification of system parameters. For a metric of baseline performance, gain-scheduled quaternion feedback control is developed. With a regularized data-weighting recursive least-squares parameter estimation algorithm, the adaptive quaternion controller is shown to be better than the baseline method in simulation and hardware results. This method is also shown to produce universal performance for all aircraft with the three conventional control surface actuators (aileron, elevator, and rudder) barring saturation and assuming accurate system identification. Testing of attitude control algorithms requires development in quaternion-based navigational control and attitude estimation. A novel technique for hover north/east position control is derived. Also, altitude tracking in hover, given an inconsistent thrust system, is addressed with an original method of on-line throttle system identification. Means for quaternion-based level flight control are produced from adaptations made to existing techniques employed in the Brigham Young University Multi-Agent Coordination and Control Lab. Also generated are simple trajectories for transitions between flight modes. A method for the estimation of quaternion attitude is developed, which uses multiple sensors combined in a filtering technique similar to the fixed-gain Kalman filter. Simulation and hardware results of these methods are presented for concept validation. A discussion of the development and production of these testing means (a simulation environment and hardware flight test system) is provided. In culmination, a fully autonomous miniature tailsitter system is produced with results demonstrating its various capabilities.

The motivation for this research is the need to improve performance of the autonomous flight of a tailsitter UAV. Tailsitter aircraft combine the hovering and vertical take-off and landing capability of a rotorcraft with the long endurance flight capability of a fixed-wing aircraft. The particular aircraft used in this research is the V-Bat, a tailsitter UAV with a conventional wing and the propeller and control surfaces located within a ducted-fan tail assembly. This research focuses on identifying the models and parameters of the V-Bat in hover and level flight as a basis for the design of the control systems for hover, level, and transition modes of flight.Models and parameters were identified from experimental data. Wind-tunnel tests, bench tests, and flight tests were performed in a variety of flight conditions. Wind tunnel tests yielded force and moment coefficients over the full flight envelope of the V-Bat. Models and parameters for longitudinal, lateral, and hover flight are presented. Bench tests were conducted to enhance understanding about the ducted-fan propulsion system and the effectiveness of the control surfaces. The thrust characteristics of the ducted fan were measured. Control derivatives were derived from force and moment measurements. Flight tests were completed to obtain dynamic models of the V-Bat in hover flight. Using frequency-domain system identification methods, frequency-response and transfer function models of roll, pitch, and yaw responses to aileron, elevator, and rudder control input were derived.The results obtained from these experimental tests were used to identify models and parameters of the V-Bat aircraft, giving insight into its behavior and enhancing the control analysis and simulation capabilities for this aircraft, thus providing the increased levels of understanding needed for autonomous flight.

Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) possess several beneficial attributes, including requiring minimal space to takeoff, hover, and land. The tailsitter is a type of VTOL airframe that combines the benefits of VTOL capability with the ability to achieve efficient horizontal flight. One type of tailsitter, the Quadrotor Biplane (QRBP), can transition the vehicle from hover as a quadrotor to horizontal flight as a biplane. The vehicle used in this thesis is a QRBP designed with special considerations for fully autonomous operation in an outdoor environment in the presence of model uncertainties. QRBPs undergo a rotation of 90° about its pitch axis during transition from vertical to horizontal flight that induces strong aerodynamic forces that are difficult to model, thus necessitating the use of a robust control method to overcome the resulting uncertainties in the model. A feedback-linearizing controller augmented with an H-Infinity robust control is developed to regulate the altitude and pitch angle of the vehicle for the whole flight regime, including the ascent, transition forward, and landing. The performance of the proposed control design is demonstrated through numerical simulations in MATLAB and outdoor flight tests. The H-Infinity controller successfully tracks the prescribed trajectory, demonstrating its value as a computationally inexpensive, robust control technique for QRBP tailsitter UAVs. / Master of Science / Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) are a special type of UAV that can takeoff, hover, and land vertically, which lends several benefits. VTOL aircraft have recently gained popularity due to their potential to serve as fast and efficient payload delivery vehicles for e-commerce. One type of VTOL aircraft, the Quadrotor Biplane (QRBP) combines the ability of a quadrotor aircraft to hover, with the efficient horizontal flight of a biplane. Such a vehicle is able to takeoff and land in confined spaces, and also travel large distances on a single battery. However, the takeoff maneuver of a QRBP involves pitching from vertical to horizontal flight, which causes the vehicle to experience strong aerodynamic effects that are difficult to accurately model. Thus, to autonomously perform this unique maneuver, a robust control technique is necessary. A robust UAV controller is one that functions even when there is a degree of uncertainty in the predicted behavior of the vehicle, such as differences between estimated and actual vehicle parameters, or the presence of external disturbances such as wind. Therefore, a robust controller known as H-Infinity is developed to regulate the altitude and pitch angle of the QRBP as it takes off, transitions to forward flight, flies as a biplane, transitions back to vertical flight, and lands. The performance of the proposed control design is validated using numerical simulations performed in MATLAB, and flight tests. The H-Infinity controller successfully tracks the prescribed trajectory, demonstrating its value as a reliable, computationally inexpensive, robust control technique for QRBP UAVs.

Tailsitter UAVs (Unmanned Aerial Vehicles) are a type of VTOL (Vertical Take off and Landing) aircraft that combines the agility of a quadrotor drone with the endurance and speed of a fixed-wing aircraft. For this reason, they have become popular in a wide range of applications from tactical surveillance to parcel delivery. This thesis details a clean sheet design process for a tailsitter UAV that includes the dynamic modeling, control design, simulation, vehicle design, vehicle prototype fabrication, and testing of a tailsitter UAV. The goal of this process was to design a robust controller that is able to handle uncertainties in the system's parameters and external disturbances and subsequently can control the vehicle through the transition between vertical and horizontal flight regimes. It is evident in the literature that most researchers choose to model and control tailsitter UAVs using separate methods for the vertical and horizontal flight regimes and combine them into one control architecture. The novelty of this thesis is the use of a single dynamical model for all flight regimes and the robust control technique used. The control algorithm used for this vehicle is a MRAC (Model Reference Adaptive Control) law, which relies on reference models and gains that adapt according to the vehicle's response in all flight regimes. To validate this controller, numerical simulations in Matlab and flight tests were conducted. The combination of these validation methods confirms our adaptive controller's ability to control the transition between the vertical and horizontal flight regimes when faced with both parametric uncertainties and external disturbances. / Master of Science / Unmanned aircrafts have been a topic of constant research and development recently due to their wide range of applications and their ability to fly without directly involving pilots. More specifically, VTOL UAVs have the advantage of being able to take off without a runway while retaining the efficiency of a classical aircraft. A tailsitter UAV behaves as a traditional quadrotor drone when in its vertical configuration and can rotate to a horizontal configuration, where it takes advantage of its wings to fly as a conventional aircraft. Modeling the dynamics of the tailsitter UAV and designing an autopilot controller is the main focus of this thesis. An adaptive controller was chosen for the tailsitter UAV due to its ability to modify the gains of the system based on the behavior of the vehicle to adapt to the unknown vehicle properties. This controller was validated using both computer simulations and actual flight tests. It was found that the adaptive controller was able to successfully control the transition between the vertical and horizontal flight regimes despite the uncertainties in the parameters of the vehicle.

Several configurations of Unmanned Aerial Vehicles (UAVs) were proposed to support different applications. One of them is the tailsitter, a fixed-wing aircraft that takes off and lands on its own tail, with the high endurance advantage from fixed-wing aircraft and, as helicopters and multicopters, not requiring a runway during takeoff and landing. However, a tailsitter has a complex operation with multiple flight stages, each one with its own particularities and requirements, which emphasises the necessity of a reliable autopilot for its use as a UAV. The literature already introduces tailsitter UAVs with complex mechanisms or with multiple counter-rotating propellers, but not one with only one propeller and without auxiliary structures to assist in the takeoff and landing. This thesis presents a tailsitter UAV, named AVALON (Autonomous VerticAL takeOff and laNding), and its autopilot, composed of 3 main units: Sensor Unit, Navigation Unit and Control Unit. In order to choose the most appropriate techniques for the autopilot, different solutions are evaluated. For Sensor Unit, Extended Kalman Filter and Unscented Kalman Filter estimate spatial information from multiple sensors data. Lookahead, Pure Pursuit and Line-of-Sight, Nonlinear Guidance Law and Vector Field path-following algorithms are extended to incorporate altitude information for Navigation Unit. In addition, a structure based on classical methods with decoupled Proportional-Integral-Derivative controllers is compared to a new control structure based on dynamic inversion. Together, all these techniques show the efficacy of AVALONs autopilot. Therefore, AVALON results in a small electric tailsitter UAV with a simple design, with only one propeller and without auxiliary structures to assist in the takeoff and landing, capable of executing all flight stages. / Diversas configurações de Veículos Aéreos Não Tripulados (VANTs) foram propostas para serem utilizadas em diferentes aplicações. Uma delas é o tailsitter, uma aeronave de asa fixa capaz de decolar e pousar sobre a própria cauda. Esse tipo de aeronave apresenta a vantagem de aeronaves de asa fixa de voar sobre grandes áreas com pouco tempo e bateria e, como helicópteros e multicópteros, não necessita de pista para decolar e pousar. Porém, um tailsitter possui uma operação complexa, com múltiplos estágios de voo, cada um com suas peculiaridades e requisitos, o que enfatiza a necessidade de um piloto automático confiável para seu uso como um VANT. A literatura já introduz VANTs tailsitters com mecanismos complexos ou múltiplos motores contra-rotativos, mas não com apenas um motor e sem estruturas para auxiliar no pouso e na decolagem. Essa tese apresenta um VANT tailsitter, chamado AVALON (Autonomous VerticAL takeOff and laNding), e seu piloto automático, composto por 3 unidades principais: Unidade Sensorial, Unidade de Navegação e Unidade de Controle. Diferentes soluções são avaliadas para a escolha das técnicas mais apropriadas para o piloto automático. Para a Unidade Sensorial, Extended Kalman Filter e Unscented Kalman Filter estimam a informação espacial de múltiplos dados de diversos sensores. Os algoritmos de seguimento de trajetória Lookahead, Pure Pursuit and Line-of-Sight, Nonlinear Guidance Law e Vector Field são estendidos para considerar a informação da altitude para a Unidade de Navegação. Além do mais, uma estrutura baseada em métodos clássicos com controladores Proporcional- Integral-Derivativo desacoplados é comparada a uma nova estrutura de controle baseada em dinâmica inversa. Juntas, todas essas técnicas demonstram a eficácia do piloto automático do AVALON. Portanto, AVALON resulta em um VANT tailsitter pequeno e elétrico, com um design simples, apenas um motor e sem estruturas para auxiliar o pouso e a decolagem, capaz de executar todos os estágios de voo.

Several configurations of Unmanned Aerial Vehicles (UAVs) were proposed to support different applications. One of them is the tailsitter, a fixed-wing aircraft that takes off and lands on its own tail, with the high endurance advantage from fixed-wing aircraft and, as helicopters and multicopters, not requiring a runway during takeoff and landing. However, a tailsitter has a complex operation with multiple flight stages, each one with its own particularities and requirements, which emphasises the necessity of a reliable autopilot for its use as a UAV. The literature already introduces tailsitter UAVs with complex mechanisms or with multiple counter-rotating propellers, but not one with only one propeller and without auxiliary structures to assist in the takeoff and landing. This thesis presents a tailsitter UAV, named AVALON (Autonomous VerticAL takeOff and laNding), and its autopilot, composed of 3 main units: Sensor Unit, Navigation Unit and Control Unit. In order to choose the most appropriate techniques for the autopilot, different solutions are evaluated. For Sensor Unit, Extended Kalman Filter and Unscented Kalman Filter estimate spatial information from multiple sensors data. Lookahead, Pure Pursuit and Line-of-Sight, Nonlinear Guidance Law and Vector Field path-following algorithms are extended to incorporate altitude information for Navigation Unit. In addition, a structure based on classical methods with decoupled Proportional-Integral-Derivative controllers is compared to a new control structure based on dynamic inversion. Together, all these techniques show the efficacy of AVALONs autopilot. Therefore, AVALON results in a small electric tailsitter UAV with a simple design, with only one propeller and without auxiliary structures to assist in the takeoff and landing, capable of executing all flight stages. / Diversas configurações de Veículos Aéreos Não Tripulados (VANTs) foram propostas para serem utilizadas em diferentes aplicações. Uma delas é o tailsitter, uma aeronave de asa fixa capaz de decolar e pousar sobre a própria cauda. Esse tipo de aeronave apresenta a vantagem de aeronaves de asa fixa de voar sobre grandes áreas com pouco tempo e bateria e, como helicópteros e multicópteros, não necessita de pista para decolar e pousar. Porém, um tailsitter possui uma operação complexa, com múltiplos estágios de voo, cada um com suas peculiaridades e requisitos, o que enfatiza a necessidade de um piloto automático confiável para seu uso como um VANT. A literatura já introduz VANTs tailsitters com mecanismos complexos ou múltiplos motores contra-rotativos, mas não com apenas um motor e sem estruturas para auxiliar no pouso e na decolagem. Essa tese apresenta um VANT tailsitter, chamado AVALON (Autonomous VerticAL takeOff and laNding), e seu piloto automático, composto por 3 unidades principais: Unidade Sensorial, Unidade de Navegação e Unidade de Controle. Diferentes soluções são avaliadas para a escolha das técnicas mais apropriadas para o piloto automático. Para a Unidade Sensorial, Extended Kalman Filter e Unscented Kalman Filter estimam a informação espacial de múltiplos dados de diversos sensores. Os algoritmos de seguimento de trajetória Lookahead, Pure Pursuit and Line-of-Sight, Nonlinear Guidance Law e Vector Field são estendidos para considerar a informação da altitude para a Unidade de Navegação. Além do mais, uma estrutura baseada em métodos clássicos com controladores Proporcional- Integral-Derivativo desacoplados é comparada a uma nova estrutura de controle baseada em dinâmica inversa. Juntas, todas essas técnicas demonstram a eficácia do piloto automático do AVALON. Portanto, AVALON resulta em um VANT tailsitter pequeno e elétrico, com um design simples, apenas um motor e sem estruturas para auxiliar o pouso e a decolagem, capaz de executar todos os estágios de voo.

There are two traditional aircraft categories: fixed-wing which have a long endurance and a high cruise airspeed and rotorcraft which can take-off and land vertically. The tailsitter is a type of aircraft that has the strengths of both platforms, with no additional mechanical complexity, because it takes off and lands vertically on its tail and can transition the entire aircraft horizontally into high-speed flight. In this dissertation, we develop the entire control system for a tailsitter with a ducted fan. The standard method to compute the quaternion-based attitude error does not generate ideal trajectories for a hovering tailsitter for some situations. In addition, the only approach in the literature to mitigate this breaks down for large attitude errors. We develop an alternative quaternion-based error method which generates better trajectories than the standard approach and can handle large errors. We also derive a hybrid backstepping controller with almost global asymptotic stability based on this error method. Many common altitude and airspeed control schemes for a fixed-wing airplane assume that the altitude and airspeed dynamics are decoupled which leads to errors. The Total Energy Control System (TECS) is an approach that controls the altitude and airspeed by manipulating the total energy rate and energy distribution rate, of the aircraft, in a manner which accounts for the dynamic coupling. In this dissertation, a nonlinear controller, which can handle inaccurate thrust and drag models, based on the TECS principles is derived. Simulation results show that the nonlinear controller has better performance than the standard PI TECS control schemes. Most constant altitude transitions are accomplished by generating an optimal trajectory, and potentially actuator inputs, based on a high fidelity model of the aircraft. While there are several approaches to mitigate the effects of modeling errors, these do not fully remove the accurate model requirement. In this dissertation, we develop two different approaches that can achieve near constant altitude transitions for some types of aircraft. The first method, based on multiple LQR controllers, requires a high fidelity model of the aircraft. However, the second method, based on the energy along the body axes, requires almost no aerodynamic information.

Vertical Take-Off and Land (VTOL) Unmanned Air Vehicles (UAVs) possess several desirable characteristics, such as being able to hover and take-off or land in confined areas. One type of VTOL airframe, the tailsitter, has all of these advantages, as well as being able to fly in the more energy-efficient level flight mode. The tailsitter can track trajectories that successfully transition between hover and level flight modes. Three methods for performing transitions are described: a simple controller, a feedback linearization controller, and an adaptive controller. An autopilot navigational state machine with appropriate transitioning between level and hover waypoints is also presented. The simple controller is useful for performing a immediate transition. It is very quick to react and maintains altitude during the maneuver, but tracking is not performed in the lateral direction. The feedback linearization controller and adaptive controller both perform equally well at tracking transition trajectories in lateral and longitudinal directions, but the adaptive controller requires knowledge of far fewer parameters.

We present a method of performing precision landings of a vertical take-off and landing (VTOL) unmanned air vehicle (UAV) with the use of an onboard vision sensor and information about the aircraft's orientation and altitude above ground level (AGL). A method for calculating the 3-dimensional location of the UAV relative to a ground target of interest is presented as well as a navigational controller to position the UAV above the target. A method is also presented to prevent the UAV from moving in a way that will cause the ground target of interest to go out of view of the UAV's onboard camera. These methods are tested in simulation and in hardware and resulting data is shown. Hardware flight testing yielded an average position estimation error of 22 centimeters. The method presented is capable of performing precision landings of VTOL UAV's with submeter accuracy.

UAVs have become an essential tool in many market segments, particularly the military where critical intelligence can be gathered by them. A tailsitter aircraft is a platform whose purpose is to efficiently merge the range and endurance of fixed-wing aircraft with the VTOL capabilities of rotorcraft and is of significant value in applications where launch and recovery area is limited or the use of launch and recovery equipment is not desirable. Developing autopilot software for a tailsitter UAV is unique in that the aircraft must be autonomously controlled over a much wider range of attitudes than conventional UAVs. Assumptions made in conventional estimation and control algorithms are not valid for tailsitter aircraft because of routine operation around gimbal lock. Quaternions are generally employed to overcome the limitations Euler angles; however, adapting the attitude representation to work at a full range of attitudes is only part of the solution. Kalman filter measurement updates and control algorithms must also work at any orientation. This research presents several methods of incorporating a magnetometer measurement into an extended Kalman filter. One method combines magnetometer and accelerometer sensor data using the solution to Wahba's problem to calculate an overall attitude measurement. Other methods correct only heading error and include using two sets of Euler angles to update the estimate, using quaternions to determine heading error and Euler angles to update the estimate, and using only quaternions to update the estimate. Quaternion feedback attitude control is widely used in tailsitter aircraft. This research also shows that in spite of its effective use in spacecraft, using the attitude error calculated via quaternions to drive flight control surfaces may not be optimal for tailsitters. It is shown that during hover when heading error is present, quaternion feedback can cause undesired behavior, particularly when the heading error is large. An alternative method for calculating attitude error called resolved tilt-twist is validated, improved, and shown to perform better than quaternion feedback. Algorithms are implemented on a commercially available autopilot and validation is performed using hardware in loop simulation. A custom interface is used to receive autopilot commands and send the autopilot simulated sensor information. The final topic covered deals with the tailsitter hovering in wind. As the tailsitter hovers, wind can cause the tailsitter to turn such that the wind is perpendicular to the wings. Wind tunnel data is taken and analyzed to explain this behavior.