156 research outputs found

    Autonomous landing of fixed-wing aircraft on mobile platforms

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    E n esta tesis se propone un nuevo sistema que permite la operación de aeronaves autónomas sin tren de aterrizaje. El trabajo está motivado por el interés industrial en aeronaves con la capacidad de volar a gran altitud, con más capacidad de carga útil y capaces de aterrizar con viento cruzado. El enfoque seguido en este trabajo consiste en eliminar el sistema de aterrizaje de una aeronave de ala fija empleando una plataforma móvil de aterrizaje en tierra. La aeronave y la plataforma deben sincronizar su movimiento antes del aterrizaje, lo que se logra mediante la estimación del estado relativo entre ambas y el control cooperativo del movimiento. El objetivo principal de esta Tesis es el desarrollo de una solución práctica para el aterrizaje autónomo de una aeronave de ala fija en una plataforma móvil. En la tesis se combinan nuevos métodos con experimentos prácticos para los cuales se ha desarrollado un sistema de pruebas específico. Se desarrollan dos variantes diferentes del sistema de aterrizaje. El primero presta atención especial a la seguridad, es robusto ante retrasos en la comunicación entre vehículos y cumple procedimientos habituales de aterrizaje, al tiempo que reduce la complejidad del sistema. En el segundo se utilizan trayectorias optimizadas del vehículo y sincronización bilateral de posición para maximizar el rendimiento del aterrizaje en términos de requerimientos de longitud necesaria de pista, pero la estabilidad es dependiente del retraso de tiempo, con lo cual es necesario desarrollar un controlador estabilizador ampliado, basado en pasividad, que permite resolver este problema. Ambas estrategias imponen requisitos funcionales a los controladores de cada uno de los vehículos, lo que implica la capacidad de controlar el movimiento longitudinal sin afectar el control lateral o vertical, y viceversa. El control de vuelo basado en energía se utiliza para proporcionar dicha funcionalidad a la aeronave. Los sistemas de aterrizaje desarrollados se han analizado en simulación estableciéndose los límites de rendimiento mediante múltiples repeticiones aleatorias. Se llegó a la conclusión de que el controlador basado en seguridad proporciona un rendimiento de aterrizaje satisfactorio al tiempo que suministra una mayor seguridad operativa y un menor esfuerzo de implementación y certificación. El controlador basado en el rendimiento es prometedor para aplicaciones con una longitud de pista limitada. Se descubrió que los beneficios del controlador basado en el rendimiento son menos pronunciados para una dinámica de vehículos terrestres más lenta. Teniendo en cuenta la dinámica lenta de la configuración del demostrador, se eligió el enfoque basado en la seguridad para los primeros experimentos de aterrizaje. El sistema de aterrizaje se validó en diversas pruebas de aterrizaje exitosas, que, a juicio del autor, son las primeras en el mundo realizadas con aeronaves reales. En última instancia, el concepto propuesto ofrece importantes beneficios y constituye una estrategia prometedora para futuras soluciones de aterrizaje de aeronaves.In this thesis a new landing system is proposed, which allows for the operation of autonomous aircraft without landing gear. The work was motivated by the industrial need for more capable high altitude aircraft systems, which typically suffer from low payload capacity and high crosswind landing sensitivity. The approach followed in this work consists in removing the landing gear system from the aircraft and introducing a mobile ground-based landing platform. The vehicles must synchronize their motion prior to landing, which is achieved through relative state estimation and cooperative motion control. The development of a practical solution for the autonomous landing of an aircraft on a moving platform thus constitutes the main goal of this thesis. Therefore, theoretical investigations are combined with real experiments for which a special setup is developed and implemented. Two different landing system variants are developed — the safety-based landing system is robust to inter-vehicle communication delays and adheres to established landing procedures, while reducing system complexity. The performance-based landing system uses optimized vehicle trajectories and bilateral position synchronization to maximize landing performance in terms of used runway, but suffers from time delay-dependent stability. An extended passivity-based stabilizing controller was implemented to cope with this issue. Both strategies impose functional requirements on the individual vehicle controllers, which imply independent controllability of the translational degrees of freedom. Energy-based flight control is utilized to provide such functionality for the aircraft. The developed landing systems are analyzed in simulation and performance bounds are determined by means of repeated random sampling. The safety-based controller was found to provide satisfactory landing performance while providing higher operational safety, and lower implementation and certification effort. The performance-based controller is promising for applications with limited runway length. The performance benefits were found to be less pronounced for slower ground vehicle dynamics. Given the slow dynamics of the demonstrator setup, the safety-based approach was chosen for first landing experiments. The landing system was validated in a number of successful landing trials, which to the author’s best knowledge was the first time such technology was demonstrated on the given scale, worldwide. Ultimately, the proposed concept offers decisive benefits and constitutes a promising strategy for future aircraft landing solutions

    A novel approach to the control of quad-rotor helicopters using fuzzy-neural networks

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    Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotor’s ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications

    Using learning from demonstration to enable automated flight control comparable with experienced human pilots

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    Modern autopilots fall under the domain of Control Theory which utilizes Proportional Integral Derivative (PID) controllers that can provide relatively simple autonomous control of an aircraft such as maintaining a certain trajectory. However, PID controllers cannot cope with uncertainties due to their non-adaptive nature. In addition, modern autopilots of airliners contributed to several air catastrophes due to their robustness issues. Therefore, the aviation industry is seeking solutions that would enhance safety. A potential solution to achieve this is to develop intelligent autopilots that can learn how to pilot aircraft in a manner comparable with experienced human pilots. This work proposes the Intelligent Autopilot System (IAS) which provides a comprehensive level of autonomy and intelligent control to the aviation industry. The IAS learns piloting skills by observing experienced teachers while they provide demonstrations in simulation. A robust Learning from Demonstration approach is proposed which uses human pilots to demonstrate the task to be learned in a flight simulator while training datasets are captured. The datasets are then used by Artificial Neural Networks (ANNs) to generate control models automatically. The control models imitate the skills of the experienced pilots when performing the different piloting tasks while handling flight uncertainties such as severe weather conditions and emergency situations. Experiments show that the IAS performs learned skills and tasks with high accuracy even after being presented with limited examples which are suitable for the proposed approach that relies on many single-hidden-layer ANNs instead of one or few large deep ANNs which produce a black-box that cannot be explained to the aviation regulators. The results demonstrate that the IAS is capable of imitating low-level sub-cognitive skills such as rapid and continuous stabilization attempts in stormy weather conditions, and high-level strategic skills such as the sequence of sub-tasks necessary to takeoff, land, and handle emergencies

    Control system development for autonomous soaring

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    Thermal and dynamic soaring are two techniques commonly used by birds to extract energy from the atmosphere. This enables them to reduce, energy used during flight and increases their endurance. The thermal soaring technique involves extraction of energy from thermal updrafts and in dynamic soaring energy is extracted from wind shear. These techniques are investigated in this thesis using point mass and non-linear 6DoF models of an unmanned powered sailplane. The key challenges of autonomous thermal soaring are the ability to identify remote thermal activity using on-board sensors and to position correctly in a thermal. In dynamic soaring, a real-time fuel saving trajectory generation technique along with a trajectory following control system is needed. A hand held IR camera was used to assess the feasibility to observe hot spots associated with thermals. The thermal positioning capability was demonstrated in a 6DoF model using a positioning algorithm. The inverse Dynamics Virtual Domain (IDVD) technique was used to generate real-time trajectories for dynamic soaring applications using a point mass model of a powered unmanned sailplane and the fuel saving trajectories were validated using a high fidelity 6DoF model and a classical controller. An important outcome of the research is the fact that energy saved during dynamic soaring flight was also realized due to a sinusoidal manoeuvre using reduced thrust. In this manoeuvre the kinetic energy is converted into potential energy by gaining altitude and by reducing airspeed. Then initial values of altitude and speed are gained by loosing the altitude. In this process a horizontal distance is travelled by using reduced thrust.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Prohibited Volume Avoidance for Aircraft

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    This thesis describes the development of a pilot override control system that prevents aircraft entering critical regions of space, known as prohibited volumes. The aim is to prevent another 9/11 style terrorist attack, as well as act as a general safety system for transport aircraft. The thesis presents the design and implementation of three core modules in the system; the trajectory generation algorithm, the trigger mechanism for the pilot override and the trajectory following element. The trajectory generation algorithm uses a direct multiple shooting strategy to provide trajectories through online computation that avoid pre-defi ned prohibited volume exclusion regions, whilst accounting for the manoeuvring capabilities of the aircraft. The trigger mechanism incorporates the logic that decides the time at which it is suitable for the override to be activated, an important consideration for ensuring that the system is not overly restrictive for a pilot. A number of methods are introduced, and for safety purposes a composite trigger that incorporates di fferent strategies is recommended. Trajectory following is best achieved via a nonlinear guidance law. The guidance logic sends commands in pitch, roll and yaw to the control surfaces of the aircraft, in order to closely follow the generated avoidance trajectory. Testing and validation is performed using a full motion simulator, with volunteers flying a representative aircraft model and attempting to penetrate prohibited volumes. The proof-of-concept system is shown to work well, provided that extreme aircraft manoeuvres are prevented near the exclusion regions. These hard manoeuvring envelope constraints allow the trajectory following controllers to follow avoidance trajectories accurately from an initial state within the bounding set. In order to move the project closer to a commercial product, operator and regulator input is necessary, particularly due to the radical nature of the pilot override system

    Disturbance observer based control with anti-windup applied to a small fixed wing UAV for disturbance rejection

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    Small Unmanned Aerial Vehicles (UAVs) are attracting increasing interest due to their favourable features; small size, low weight and cost. These features also present different challenges in control design and aircraft operation. An accurate mathematical model is unlikely to be available meaning optimal control methods become difficult to apply. Furthermore, their reduced weight and inertia mean they are significantly more vulnerable to environmental disturbances such as wind gusts. Larger disturbances require more control actuation, meaning small UAVs are far more susceptible to actuator saturation. Failure to account for this can lead to controller windup and subsequent performance degradation. In this work, numerical simulations are conducted comparing a baseline Linear Quadratic Regulator (LQR) controller to integral augmentation and Disturbance Observer Based Control (DOBC). An anti-windup scheme is added to the DOBC to attenuate windup effects due to actuator saturation. A range of external disturbances are applied to demonstrate performance. The simulations conduct manoeuvres which would occur during landing, statistically the most dangerous flight phase, where fast disturbance rejection is critical. Validation simulations are then conducted using commercial X-Plane simulation software. This demonstrates that DOBC with anti-windup provides faster disturbance rejection of both modelling errors and external disturbances

    Position Control of a Quadrotor under External Constant Disturbance

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    International audienceIn the present work, an adaptive backstepping algorithm is developed in order to counteract the effects of disturbances. These disturbances are modeled as a constant force in the translational model part and as a constant torque in the orientation model part. We make the deduction of the mathematical expression for the proposed control algorithm and also we show its performance in simulation. Additionally, we include some experiments for validating the results obtained via simulation

    Autonomous landing control of highly flexible aircraft based on Lidar preview in the presence of wind turbulence

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    This paper investigates preview-based autonomous landing control of a highly flexible flying wing model using short range Lidar wind measurements in the presence of wind turbulence. The preview control system is developed based on a reduced-order linear aeroelastic model and employs a two-loop control scheme. The outer loop employs the LADRC (linear active disturbance rejection control) and PI algorithms to track the reference landing trajectory and vertical speed, respectively, and to generate the attitude angle command. This is then used by the inner-loop using H∞ preview control to compute the control inputs to the actuators (control flaps and thrust). A landing trajectory navigation system is designed to generate real-time reference commands for the landing control system. A Lidar (light detection and ranging) simulator is developed to measure the wind disturbances at a distance in front of the aircraft, which are provided to the inner-loop H∞ preview controller as prior knowledge to improve control performance. Simulation results based on the full-order nonlinear flexible aircraft dynamic model show that the preview-based landing control system is able to land the flying wing effectively and safely, showing better control performance than the baseline landing control system (without preview) with respect to landing effectiveness and disturbance rejection. The control system’s robustness to measurement error in the Lidar system is also demonstrated
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