Αντικείμενο της εργασίας είναι ο έλεγχος του προσανατολισμού ελικοπτέρου Quadrotor με χρήση ελεγκτή PID. Το ελικόπτερο Quadrotor είναι ένα μη γραμμικό, ασταθές, υποενεργοποιούμενο σύστημα. Για αυτούς τους λόγους, ο έλεγχός του παρουσιάζει σοβαρά προβλήματα. Ο ελεγκτής PID αρχικά εφαρμόζεται στο γραμμικοποιημένο μοντέλο του συστήματος, και εν συνεχεία διακριτοποιείται και εξετάζεται στο πλήρες μη γραμμικό μοντέλο του Quadrotor. Ιδιαίτερο βάρος δίνεται στη ρύθμιση του ελεγκτή PID. Αφού παρουσιαστούν οι κυριότερες μέθοδοι ρύθμισης ενός τέτοιου ελεγκτή, επιλέγεται η μέθοδος Extremum Seeking, μία επαναληπτική μέθοδος που βελτιστοποιεί τον PID ώστε να ελαχιστοποιείται τοπικά μια συνάρτηση κόστους. Σημαντικό πλεονέκτημα αυτής της μεθόδου αποτελεί το γεγονός ότι μπορεί να εφαρμοστεί κατ' ευθείαν στο μη γραμμικό μοντέλο του συστήματος βελτιστοποιώντας περαιτέρω τον ελεγκτή. Στη συνέχεια ο ελεγκτής PID εξετάζεται σε ένα πραγματικό ελικόπτερο που κατασκευάστηκε στο εργαστήριο. Στο πειραματικό αυτό σύστημα, η υλοποίηση του PID γίνεται σε έναν ηλεκτρονικό υπολογιστή, με τη βοήθεια του προγράμματος Labview ενώ η επικοινωνία ανάμεσα στον υπολογιστή και στο ελικόπτερο επιτυγχάνεται με τη βοήθεια σειριακής θύρας RS232. Μετά τη διεξαγωγή των πειραμάτων και την αξιολόγηση της απόδοσης του ελεγκτή PID, αναφέρονται τα γενικότερα συμπεράσματα της εργασίας, καθώς και προτάσεις για περαιτέρω έρευνα. / This thesis focuses on attitude control of a quadrotor helicopter with PID technique. Quadrotor is a non linear, unstable, underactuated system, so the controller design is a very challenging task. Initially the PID controller is applied to the linearized model of the helicopter, and then to the discretized one, because the controller is later implemented on a personal computer. Then we describe some PID tuning techniques that are often used in practice. In this thesis we use Extemum Seeking which is an iterative, optimization method for the PID tuning that can be used in either linear or non linear models. So Extremum Seeking can be applied to the full non linear model of the quadrotor to further improve the PID parameters. Finally the PID controller is applied to a real Quadrotor helicopter. The controller is implemented on Labview while the communication between the PC and the helicopter is achieved with two RS232 links.

Inspiré par les limitations de contrôleurs PID traditionnels et les différentes performances dans les cas idéals et réalistes, les quadrotors existants, leurs applications et leurs méthodes de contrôle ont été intensivement étudiés dans cette thèse. De nombreux challenges sont dévoilés: les systèmes embarqués ont des limites des ressources de calcul et de l'énergie; la dynamique est assez complexe et souvent mal connu; l'environnement a beaucoup de perturbations et d'incertitudes; de nombreuses méthodes de contrôle ont été proposées dans des scénarios idéaux dans la littérature sans comparaison avec d’autres méthodes. Par conséquent, cette thèse porte sur ces principaux points dans le contrôle de quadrotors.Tout d'abord, les modèles cinématiques et dynamiques sont proposés, y compris toutes les forces et couples aérodynamiques importants. Un modèle dynamique simplifié est également proposé pour certaines applications. Ensuite, la dynamique de quadrotor est analysée. En utilisant la théorie de la forme normale, le modèle de quadrotor est simplifié à une forme plus simple nommée la forme normale, qui présente toutes les propriétés dynamiques possibles du système d'origine. Les bifurcations de cette forme normale sont étudiées, et le système est simplifié à son point de bifurcation en utilisant la théorie de la variété du centre. Basé sur l’étude des applications de quadrotors, cinq scénarios réalistes sont proposés : un cas idéal, les cas avec la perturbation du vent, les incertitudes des paramètres, les bruits de capteurs et les fautes de moteur. Ces cas réalistes peuvent montrer plus globalement les performances des méthodes de contrôle par rapport aux cas idéaux. Un schéma déclenché par événements est également proposé avec le schéma déclenché par. Ensuite, la commande sans modèle est présentée, Il s'agit d'une technique simple mais efficace pour la dynamique non-linéaire, inconnue ou partiellement connue. La commande par backstepping et la commande par mode glissant sont également proposées pour la comparaison.Toutes les méthodes de contrôle sont mises en œuvre sous les schémas déclenchés par temps et par événements dans cinq scénarios différents. Basé sur l’étude des applications de quadrotors, dix critères sont choisis pour évaluer les performances des méthodes de contrôle, telles que l'erreur maximale absolue de suivi, la variance de l'erreur, le nombre d’actionnement, la consommation d'énergie, etc. / Inspired by the limitations of traditional PID controllers and the different performance in ideal and realistic cases, the existing quadrotors, their applications and control methods have been intensively studied in this dissertation. Many challenges are shown: embedded quadrotor systems have limit computational resources and energy; the aerodynamic dynamics is rather complex and poorly known; environment has many disturbances and uncertainties; many control methods have been proposed in ideal scenarios in literature without comparison. Therefore, this dissertation focuses on these main points in control of quadrotors.A kinematic model and a dynamic model are proposed, including all the important aerodynamic forces and moments. A simplified dynamic model is also given based on some applications. Then, the dynamics of quadrotor is analyzed. Using the normal form theory, the model of quadrotor is simplified to a simplest form named the normal form, which exhibits all possible dynamic properties of the original system. The bifurcations of its normal form are then studied, and the system can be further simplified at its bifurcation point using the center manifold theory.Based on the research of the applications in the first chapter, five typical realistic scenarios are proposed: an ideal case, the cases with wind disturbance, parameter uncertainties, sensor noises and actuator faults. These realistic cases can show comprehensively the performance of control methods respect to the ideal cases. An event triggered scheme is also proposed with the time triggered scheme in order to further save computational resources. Then, a newly proposed method the model free control is presented. It is a simple but efficient technique for the nonlinear, unknown or partially known dynamics. A backstepping control and a sliding mode control are also proposed for the sake of comparison.All the control methods are implemented in the time and event triggered schemes in five different scenarios. In order to keep closer to realistic situations, the control gains of each methods are not changed in different scenarios. Based on the study in the first chapter, ten criteria are chosen for measuring the performance of control methods, such as the maximum absolute tracking error, the error variance, the actuation steps, the energy consumption, etc.

Precision landing capability is a necessary development that must take place before unmanned aircraft systems (UAS) can realize their full potential in today's modern society. Current multirotor UAS are heavily reliant on GPS data to provide positioning information for landing. While generally accurate to within several meters, much higher levels of accuracy are needed to ensure safe and trouble-free operations in several UAS applications that are currently being pursued. Examples of these applications include package delivery, automatic docking and recharging, and landing on moving vehicles. The specific problem we consider is that of precision landing of a multirotor unmanned aircraft on a small barge at sea---which presents several significant challenges. Not only must we land on a moving vehicle, but the vessel also experiences random rotational and translational motion as a result of waves and wind. Because maritime operations often span long periods of time, it is also desirable that precision landing can occur at any time---day or night.In this work we present a complete approach for precision shipboard landing and address each of the aforementioned challenges. Our method is enabled by leveraging an on-board camera and a specialized landing target which can be detected in light or dark conditions. Features belonging to the target are extracted from camera imagery and are used to compute image-based visual servoing velocity commands that lead to precise alignment between the multirotor and landing target. To enable the multirotor to match the horizontal velocities of the barge, an extended Kalman filter is used to generate feed-forward velocity reference commands. The complete landing procedure is guided by a state machine architecture that incorporates corrections to account for wind, and is also capable of quickly reacquiring the landing target in a loss event. Our approach is thoroughly validated through full-scale outdoor flight tests and is shown to be reliable, timely, and accurate to within 4 to 10 centimeters.

[pt] Com recentes avanços em poder computacional, o uso de novos modelos de controle complexos se tornou viável para realizar o controle de quadrotores. Um destes métodos é o aprendizado por reforço profundo (do inglês, Deep Reinforcement Learning, DRL), que pode produzir uma política de controle que atende melhor as não-linearidades presentes no modelo do quadrotor que um método de controle tradicional. Umas das não-linearidades importantes presentes em veículos aéreos transportadores de carga são as propriedades variantes no tempo, como tamanho e massa, causadas pela adição e remoção de carga. A abordagem geral e domínio-agnóstica de um controlador por DRL também o permite lidar com navegação visual, na qual a estimação de dados de posição é incerta. Neste trabalho, aplicamos um algorítmo de Soft Actor- Critic com o objeivo de projetar controladores para um quadrotor a fim de realizar tarefas que reproduzem os desafios citados em um ambiente virtual. Primeiramente, desenvolvemos dois controladores de condução por waypoint: um controlador de baixo nível que atua diretamente em comandos para o motor e um controlador de alto nível que interage em cascata com um controlador de velocidade PID. Os controladores são então avaliados quanto à tarefa proposta de coleta e alijamento de carga, que, dessa forma, introduz uma variável variante no tempo. Os controladores concebidos são capazes de superar o controlador clássico de posição PID com ganhos otimizados no curso proposto, enquanto permanece agnóstico em relação a um conjunto de parâmetros de simulação. Finalmente, aplicamos o mesmo algorítmo de DRL para desenvolver um controlador que se utiliza de dados visuais para completar um curso de corrida em uma simulação. Com este controlador, o quadrotor é capaz de localizar portões utilizando uma câmera RGB-D e encontrar uma trajetória que o conduz a atravessar o máximo possível de portões presentes no percurso. / [en] With recent advances in computational power, the use of novel, complex control models has become viable for controlling quadrotors. One such method is Deep Reinforcement Learning (DRL), which can devise a control policy that better addresses non-linearities in the quadrotor model than traditional control methods. An important non-linearity present in payload carrying air vehicles are the inherent time-varying properties, such as size and mass, caused by the addition and removal of cargo. The general, domain-agnostic approach of the DRL controller also allows it to handle visual navigation, in which position estimation data is unreliable. In this work, we employ a Soft Actor-Critic algorithm to design controllers for a quadrotor to carry out tasks reproducing the mentioned challenges in a virtual environment. First, we develop two waypoint guidance controllers: a low-level controller that acts directly on motor commands and a high-level controller that interacts in cascade with a velocity PID controller. The controllers are then evaluated on the proposed payload pickup and drop task, thereby introducing a timevarying variable. The controllers conceived are able to outperform a traditional positional PID controller with optimized gains in the proposed course, while remaining agnostic to a set of simulation parameters. Finally, we employ the same DRL algorithm to develop a controller that can leverage visual data to complete a racing course in simulation. With this controller, the quadrotor is able to localize gates using an RGB-D camera and devise a trajectory that drives it to traverse as many gates in the racing course as possible.