Backstepping sliding-mode control of stratospheric airships using disturbance-observer

In the presence of unknown disturbances and model parameter uncertainties, this paper develop a nonlinear backstepping sliding-mode controller (BSMC) for trajectory tracking control of a stratospheric airship using a disturbance-observer (DO). Compared with the conventional sliding mode surface (SMS) constructed by a linear combination of the errors, the new SMS manifold is selected as the last back-step error to improve independence of the adjustment of the controller gains. Furthermore, a nonlinear disturbance-observer is designed to process unknown disturbance inputs and improve the BSMC performances. The closed-loop system of trajectory tracking control plant is proved to be globally asymptotically stable by using Lyapunov theory. By comparing with traditional backstepping control and SMC design, the results obtained demonstrate the capacity of the airship to execute a realistic trajectory tracking mission, even in the presence of unknown disturbances, and aerodynamic coefficient uncertaintie

Estimation of airship states and model uncertainties using nonlinear estimators

This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1− uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out

Planification et commande d'une plate-forme aéroportée stationnaire autonome dédiée à la surveillance des ouvrages d'art

Today, the inspection of structures is carried out through visual assessments effectedby qualified inspectors. This procedure is very expensive and can put the personal indangerous situations. Consequently, the development of an unmanned aerial vehicleequipped with on-board vision systems is privileged nowadays in order to facilitate theaccess to unreachable zones.In this context, the main focus in the thesis is developing original methods to deal withplanning, reference trajectories generation and tracking issues by a hovering airborneplatform. These methods should allow an automation of the flight in the presence of airdisturbances and obstacles. Within this framework, we are interested in two kinds ofaerial vehicles with hovering capacity: airship and quad-rotors.Aujourd'hui, l'inspection des ouvrages d'art est réalisée de façon visuelle par des contrôleurs sur l'ensemble de la structure. Cette procédure est coûteuse et peut être particulièrement dangereuse pour les intervenants. Pour cela, le développement du système de vision embarquée sur des drones est privilégié ces jours-ci afin de faciliter l'accès aux zones dangereuses.Dans ce contexte, le travail de cette thèse porte sur l'obtention des méthodes originales permettant la planification, la génération des trajectoires de référence, et le suivi de ces trajectoires par une plate-forme aéroportée stationnaire autonome. Ces méthodes devront habiliter une automatisation du vol en présence de perturbations aérologiques ainsi que des obstacles. Dans ce cadre, nous nous sommes intéressés à deux types de véhicules aériens capable de vol stationnaire : le dirigeable et le quadri-rotors.Premièrement, la représentation mathématique du véhicule volant en présence du vent a été réalisée en se basant sur la deuxième loi de Newton. Deuxièmement, la problématique de génération de trajectoire en présence de vent a été étudiée : le problème de temps minimal est formulé, analysé analytiquement et résolu numériquement. Ensuite, une stratégie de planification de trajectoire basée sur les approches de recherche opérationnelle a été développée.Troisièmement, le problème de suivi de trajectoire a été abordé. Une loi de commande non-linéaire robuste basée sur l'analyse de Lyapunov a été proposée. En outre, un pilote automatique basée sur les fonctions de saturations pour un quadri-rotors a été développée.Les méthodes et algorithmes proposés dans cette thèse ont été validés par des simulations

Aerial collective systems

Deployment of multiple flying robots has attracted the interest of several research groups in the recent times both because such a feat represents many interesting scientific challenges and because aerial collective systems have a huge potential in terms of applications. By working together, multiple robots can perform a given task quicker or more efficiently than a single system. Furthermore, multiple robots can share computing, sensing and communication payloads thus leading to lighter robots that could be safer than a larger system, easier to transport and even disposable in some cases. Deploying a fleet of unmanned aerial vehicles instead of a single aircraft allows rapid coverage of a relatively larger area or volume. Collaborating airborne agents can help each other by relaying communication or by providing navigation means to their neighbours. Flying in formation provides an effective way of decongesting the airspace. Aerial swarms also have an enormous artistic potential because they allow creating physical 3D structures that can dynamically change their shape over time. However, the challenges to actually build and control aerial swarms are numerous. First of all, a flying platform is often more complicated to engineer than a terrestrial robot because of the inherent weight constraints and the absence of mechanical link with any inertial frame that could provide mechanical stability and state reference. In the first section of this chapter, we therefore review this challenges and provide pointers to state-of-the-art methods to solve them. Then as soon as flying robots need to interact with each other, all sorts of problems arise such as wireless communication from and to rapidly moving objects and relative positioning. The aim of section 3 is therefore to review possible approaches to technically enable coordination among flying systems. Finally, section 4 tackles the challenge of designing individual controllers that enable a coherent behavior at the level of the swarm. This challenge is made even more difficult with flying robots because of their 3D nature and their motion constraints that are often related to the specific architectures of the underlying physical platforms. In this third section is complementary to the rest of this book as it focusses only on methods that have been designed for aerial collective systems

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Aeronautical engineering: A continuing bibliography with indexes (supplement 267)

This bibliography lists 661 reports, articles, and other documents introduced into the NASA scientific and technical information system in June, 1991. Subject coverage includes design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; theoretical and applied aspects of aerodynamics and general fluid dynamics; electrical engineering; aircraft control; remote sensing; computer sciences; nuclear physics; and social sciences

Design of autonomous sustainable unmanned aerial vehicle - A novel approach to its dynamic wireless power transfer

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Electric UAVs are presently being used widely in civilian duties such as security, surveillance, and disaster relief. The use of Unmanned Aerial Vehicle (UAV) has increased dramatically over the past years in different areas/fields such as marines, mountains, wild environments. Nowadays, there are many electric UAVs development with fast computational speed and autonomous flying has been a reality by fusing many sensors such as camera tracking sensor, obstacle avoiding sensor, radar sensor, etc. But there is one main problem still not able to overcome which is power requirement for continuous autonomous operation. When the operation needs more power, but batteries can only give for 20 to 30 mins of flight time. These types of system are not reliable for long term civilian operation because we need to recharge or replace batteries by landing the craft every time when we want to continue the operation. The large batteries also take more loads on the UAV which is also not a reliable system. To eliminate these obstacles, there should a recharging wireless power station in ground which can transmit power to these small UAVs wirelessly for long term operation. There will be camera attached in the drone to detect and hover above the Wireless Power Transfer device which got receiving and transmitting station can be use with deep learning and sensor fusion techniques for more reliable flight operations. This thesis explores the use of dynamic wireless power to transfer energy using novel rotating WPT charging technique to the UAV with improved range, endurance, and average speed by giving extra hours in the air. The hypothesis that was created has a broad application beyond UAVs. The drone autonomous charging was mostly done by detecting a rotating WPT receiver connected to main power outlet that served as a recharging platform using deep neural vision capabilities. It was the purpose of the thesis to provide an alternative to traditional self-charging systems that relies purely on static WPT method and requires little distance between the vehicle and receiver. When the UAV camera detect the WPT receiving station, it will try to align and hover using onboard sensors for best power transfer efficiency. Since this strategy relied on traditional automatic drone landing technique, but the target is rotating all the time which needs smart approaches like deep learning and sensor fusion. The simulation environment was created and tested using robot operating system on a Linux operating system using a model of the custom-made drone. Experiments on the charging of the drone confirmed that the intelligent dynamic wireless power transfer (DWPT) method worked successfully while flying on air

Aeronautical engineering: A continuing bibliography with indexes (supplement 295)

This bibliography lists 581 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in Sep. 1993. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Planification de trajectoire sous contraintes d'aéronef

The focus of this PhD thesis is on the trajectory planning module as a part of autonomous aircraft system. Feasible trajectories for aircraft flying in environment cluttered by obstacles are studied. Since aircraft dynamics are complex, nonlinear and nonholonomic; trajectory planning for such systems is very difficult and challenging.Rapidly-exploring Random Tree or RRT path planner is used as a basis to find a feasible trajectory. The advantage of this algorithm is that it does not consider only the complete vehicle model but also the environment. Two algorithms are developed to find a feasible and optimal solution. The RRT algorithm, combined with a preprocessing of the exploration space, is used for a complete realistic model of the system. However, this approach does not consider any optimal criteria. In order to consider performance criteria, the RRT* algorithm is used based on a simplified model with the help of the artificial potential field as a heuristic to improve the convergence rate to the solution.The algorithms are simulated in an application of hypersonic aerial vehicles, for example, interceptor missiles flying in high altitude. This makes the aerodynamically controlled aircraft have less maneuverability since the air density decreases exponentially with altitude. 3D shortest paths are developed and used as a metric. Therefore, a feasible and optimal trajectory is obtained efficiently. With these results, real-time constraints will be easier to verify if the algorithm is implemented on board the vehicle. In future work, replanning will be considered to improve the performance of the algorithm in case of dynamic environment or changes in the mission.Le sujet de cette thèse porte sur la planification de trajectoire pour un aéronef autonome. Les trajectoires d'aéronefs se déplaçant dans un environnement encombré par des obstacles sont étudiées. La dynamique des aéronefs étant complexe, non linéaire, et non holonome, la planification de trajectoire de ce type de systèmes est un problème très difficile.L'algorithme Rapidly-exploring Random Tree, ou RRT, est utilisé comme planificateur de base. L'avantage de cet algorithme est qu'il permet de considérer des modèles d'aéronefs complets dans un environnement complexe. Deux algorithmes sont développés pour trouver une solution faisable et optimale. Pour un modèle complet, L'algorithme RRT avec un prétraitement de l'espace d'état est utilisé dans le cas d'une prise en compte du modèle complet du système. Cependant, cette méthode ne considère pas de critères optimaux. Pour y remédier, l'algorithme RRT* est utilisé pour un modèle simplifié du système avec l'aide de champs de potentiels artificiels comme heuristique pour améliorer le taux de convergence vers la solution.Les algorithmes sont simulés pour une application d'aéronefs hypersoniques, comme par exemple des missiles intercepteurs volants à haute altitude. Les aéronefs ont donc moins de manœuvrabilité parce que la densité de l'air diminue exponentiellement avec l'altitude. Les chemins les plus courts en 3D sont développés et utilisés comme une métrique. Des trajectoires réalisables et optimales sont obtenues efficacement. A partir de ces résultats, les contraintes de temps réel à bord du véhicule seront plus faciles à vérifier. Dans les travaux futurs, la replanification sera considérée pour améliorer la performance de l'algorithme en cas d'environnement dynamique ou de changements dans la mission