The control of systems with uncertain nonlinear dynamics is an important field of control science attracting decades of focus. In this dissertation, four different control strategies are presented using sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in unsteady flow. In Chapter 3, a continuous robust control design is proposed for a class of single input and single output system with uncertainties. An aeroelastic system with a trailingedge flap as its control input will be considered as the plant for demonstration of effectiveness of the controller. The controller is proved to be robust by both athematical proof and simulation results. In Chapter 3, a robust output feedback control strategy is discussed for the vibration suppression of an aeroelastic system operating in an unsteady incompressible flowfield. The aeroelastic system is actuated using a combination of leading-edge (LE) and trailing-edge (TE) flaps in the presence of different kinds of gust disturbances. In Chapter 5, a neural-network based model-free controller is designed for an aeroelastic system operating at supersonic speed. The controller is shown to be able to effectively asymptotically stabilize the system via both a Lyapunov-based stability proof and numerical simulation results.

This work considers an aerial robot system composed of an Unmanned Aerial Vehicle (UAV) and a rigid manipulator, to be employed in mobile manipulation tasks. The strategy adopted for accomplishing the aerial manipulation is a decomposition of the previous system in two decoupled subsystems: one concerning the center of mass of the aerial robot; and another concerning the manipulator's orientation. Two Lyapunov-based controllers are developed, using a back stepping procedure, for solving the trajectory tracking problems related to the two subsystems. In the controller design, three inputs are assumed available: a translational acceleration along a body direction of the UAV; an angular velocity vector of this body rotation; and, finally, a torque at the spherical, or revolute, joint connecting the UAV and the manipulator. The first two inputs are generated by the same controller in order to drive the center of mass on a desired trajectory; while a second controller drives, through the third input, the manipulator's orientation to track a desired orientation. Formal stability proofs are provided that guarantee asymptotic trajectory tracking. Finally, the proposed control strategy is experimentally tested and validated.

Ce travail étudie certains des problèmes les plus pertinents dans le sens de la navigation et contrôle présentés dans une classe particulière de mini-véhicules aériens. L'un des principaux objectifs c'est à réaliser un véhicule léger et facile à déployer dans un court laps de temps, un véhicule sans pilote drone capable de suivre une mission complète, du décollage aux points de cheminement suivants et de terminer la mission avec un atterrissage autonome à l'intérieur d'une zone délimitée en utilisant une interface graphique dans un ordinateur ou une tablette. La génération de trajectoire II est la partie qui dit le drone où il doit voyager et sont générés par un algorithme intégré sur le drone. Le résultat classique de Dubins est utilisé comme base pour la génération de trajectoire en 2D et nous avons étendu à la génération de trajectoire 3D. Une stratégie de suivi de trajectoire développée en utilisant l'approche de Lyapunov, est présentée pour piloter un drone à voilure fixe à travers tout le chemin désiré. Le concept clé derrière le contrôleur de suivi de trajectoire s'appuie sur la réduction de la distance entre le centre de masse de l'avion p et le point sur la trajectoire q à zéro, ainsi que l'angle entre le vecteur vitesse et la tangente à la trajectoire. Afin de tester les techniques mises au point au cours de la thèse une application C# -Net personnalisée a été développé nommé MAV3DSim (Multi-Aerial Vehicle 3D Simulator). Le MAV3DSim permet une opération de lecture/écriture de/vers le moteur de simulation à partir de laquelle nous pourrions recevoir toutes les informations de capteurs émulés et envoyés par le simulateur. Le système complet est capable d'effectuer un décollage et d'atterrissage autonome, à travers des points de suivi. Ceci est accompli en utilisant chacune des stratégies développées au cours de la thèse. Nous avons une stratégie pour le décollage et l'atterrissage, ce qui est généré par la partie de navigation qui est le générateur de trajectoire. Une fois que nous avons généré le chemin, il est utilisé par la stratégie de suivi de trajectoire et avec ce que nous avons l'atterrissage et le décollage autonome. / This work studies some of the most relevant problems in the direction of navigation and control presented in a particular class of mini‐aircraft. One of the main objectives is to build a lightweight and easy to deploy vehicle in a short period of time, an unmanned aerial vehicle capable of following a complete mission from take‐o⁄ to the following waypoints and complete the mission with an autonomous landing within a delimitated area using a graphical interface in a computer. The Trajectory Generation It is the part that tells the drone where it must travel and are generated by an algorithm built into the drone. The classic result of Dubins is used as a basis for the trajectory generation in 2D and we have extended it to the 3D trajectory generation. A path following strategy developed using the Lyapunov approach is presented to pilot a fixed wing drone across the desired path. The key concept behind the tracking controller is the reduction of the distance between the center of mass of the aircraft p and the point q on the path to zero, as well as the angle between the velocity vector and the vector tangent to the path. In order to test the techniques developed during the thesis a customized C # .Net application was developed called MAV3DSim (Multi‐Aerial Vehicle 3D Simulator). The MAV3DSim allows a read / write operation from / to the simulation engine from which we could receive all emulated sensor information and sent to the simulator. The MAV3DSim consists of three main elements, the simulation engine, the computation of the control law and the visualization interface. The simulation engine is in charge of the numeric integration of the dynamic equations of the vehicle, we can choose between a quadrotor and a xed wing drone for use in simulation. The visualization interface resembles a ground station type of application, where all variables of the vehicle s state vector can be represented on the same screen. The experimental platform functions as a test bed for the control law prototyping. The platform consists of a xed wing aircraft with a PX4 which has the autopilot function as well as a Raspberry PI mini‐computer which to the implementation of the generation and trajectory tracking. The complete system is capable of performing an autonomous take‐o⁄and landing, through waypoints. This is accomplished by using each of the strategies developed during the thesis. We have a strategy for take‐o⁄ and landing, which is generated by the navigationon part that is the trajectory generator. Once we have generated the path, it is used by the trajectory tracking strategy and withthat we have landing and take‐o⁄ autonomously.

In this thesis I propose methods and strategies for the design of advanced model predictive control designs. The contributions are in the areas of data-driven model based MPC, model monitoring and explicit incorporation of closed-loop response considerations in the MPC, while handling issues such as plant-model mismatch, constraints and uncertainty. In the initial phase of this research, I address the problem of handling plant-model mismatch by designing a subspace identification based MPC framework that includes model monitoring and closed-loop identification components. In contrast to performance monitoring based approaches, the validity of the underlying model is monitored by proposing two indexes that compare model predictions with measured past output. In the event that the model monitoring threshold is breached, a new model is identified using an adapted closed-loop subspace identification method. To retain the knowledge of the nominal system dynamics, the proposed approach uses the past training data and current input, output and set-point as the training data for re-identification. A model validity mechanism then checks if the new model predictions are better than the existing model, and if they are, then the new model is utilized within the MPC. Next, the proposed MPC with re-identification method is extended to batch processes. To this end, I first utilize a subspace-based model identification approach for batch processes to be used in model predictive control. A model performance index is developed for batch process, then in the case of poor prediction, re-identification is triggered to identify a new model. In order to emphasize on the recent batch data, the identification is developed in order to increase the contribution of the current data. In another direction, the stability of data driven predictive control is addressed. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI) model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. Finally, I address the problem of control of nonlinear systems to deliver a prescribed closed-loop behavior. In particular, the framework allows for the practitioner to first specify the nature and specifics of the desired closed-loop behavior (e.g., first order with smallest time constant, second order with no more than a certain percentage overshoot, etc.). An optimization based formulation then computes the control action to deliver the best attainable closed loop behavior. To decouple the problems of determining the best attainable behavior and tracking it as closely as possible, the optimization problem is posed and solved in two tiers. In the first tier, the focus is on determining the best closed-loop behavior attainable, subject to stability and tracking constraints. In the second tier, the inputs are tweaked to possibly improve the tracking of the optimal output trajectories given by the first tier. The effectiveness of all of the proposed methods are illustrated through simulations on nonlinear systems. / Dissertation / Doctor of Philosophy (PhD)

La complexité inhérente à la coordination des mouvements d'un groupe de robots mobiles est traitée en investiguant plus avant les potentialités des architectures de contrôle comportementales dont le but est de briser la complexité des tâches à exécuter. En effet, les robots mobiles peuvent évoluer dans des environnements très complexes et nécessite de surcroît une coopération précise et sécurisée des véhicules pouvant rapidement devenir inextricable. Ainsi, pour maîtriser cette complexité, le contrôleur dédié à la réalisation de la tâche est décomposé en un ensemble de comportements/contrôleurs élémentaires (évitement d'obstacles et de collision entre les robots, attraction vers une cible, etc.) qui lient les informations capteurs (provenant de caméras, des capteurs locaux du robot, etc.) aux actionneurs des différentes entités robotiques. La tâche considérée est la navigation en formation en présence d'obstacles (statiques et dynamiques). La spécificité de l'approche théorique consiste à allier les avantages des architectures de contrôle comportementales à la méthode de la structure virtuelle où le groupe de robots mobiles suit un corps virtuel avec une dynamique (vitesse, direction) donnée. Ainsi, l'activation d'un comportement élémentaire en faveur d'un autre se fait en respectant les contraintes structurelles des robots (e.g. vitesses et accélérations maximales, etc.) en vue d'assurer le maximum de précision et de sécurité des mouvements coordonnés entre les différentes entités mobiles. La coopération consiste à se partager les places dans la structure virtuelle de manière distribuée et de façon à atteindre plus rapidement la formation désirée. Pour garantir les critères de performances visés par l'architecture de contrôle, les systèmes hybrides qui permettent de commander des systèmes continus en présence d'évènements discrets sont exploités. En effet, ces contrôleurs (partie discrète) permettent de coordonner l'activité des différents comportements (partie continue) disponibles au niveau de l'architecture, tout en offrant une analyse automaticienne rigoureuse de la stabilité de celle-ci au sens de Lyapunov. Chaque contribution est illustrée par des résultats de simulation. Le dernier chapitre est dédié à l'implémentation de l'architecture de contrôle proposée sur un groupe de robots mobiles Khepera III. / Inherent difficulty of coordinating a group of mobile robots is treated by investigating behavior-based architectures which aim to break task complexity. In fact, multi-robot navigation may become rapidly inextricable, specifically if it is made in hazardous and dynamical environment. The considered task is the navigation in formation in presence of (static and dynamic) obstacles. To overcome its complexity, it is proposed to divide the overall task into two basic behaviors/controllers (obstacle avoidance, attraction to a dynamical target). Applied control is chosen among these controllers according to sensors information (camera, local sensors, etc.). Theoretic approach combines behavior-based and the virtual structure strategy which considers the formation as a virtual body with a given dynamic (velocity, direction). Thus, activating a controller or another is accomplished while respecting structural robots constraints (e.g. maximal velocities and accelerations). The objective is to insure the highest precision and safety of the coordinated motion between the robots. These ones cooperate by optimizing the way of sharing their places in the formation in order to form it in a faster manner. To guarantee performance criteria of the control architecture, hybrid systems tolerating the control of continuous systems in presence of discrete events are explored. In fact, this control allows coordinating (by discrete part) the different behaviors (continuous part) of the architecture. A complete analysis of this architecture stability is also given thanks to Lyapunov-based theory. Every contribution is illustrated through simulation results. The last chapter is devoted to the implementation of the proposed control architecture on a group of Khepera III robots.

Cette thèse étudie certains problèmes plus importants dans le sens de guidage, navigation et contrôle présentés dans une catégorie particulière de mini véhicules aériens (MVA) : le MVA convertible avec des ailes fixes et disques pendulaires. Cet aéronef est capable de changer sa configuration de vol, du vol stationnaire au vol palier et vice versa, au moyen d’une manœuvre de transition. Motivé par des applications civiles, on étudie théoriquement et expérimentalement les principes de contrôle en fonction de Lyapunov pour les dynamiques présentées dans le MVA convertible. Des résultats de convergence asymptotique sont obtenus sur l’enveloppe de vol complet du véhicule : d’un vol vertical à basse vitesse à un vol vers l’avant à grande vitesse. Cette thèse est divisée en quatre parties principales : l’étude de 1) les aéronefs à voilure fixe ; 2) le quadrirotor (avion équipe de quatre moteurs) ; 3) l’aéronef convertible ; 4) les applications de vision en utilisant l’aéronef convertible. Dans la première partie, un principe de contrôle en fonction de Lyapunov est développé pour diriger un mini véhicule aérien à voilure fixe tout au long d’un chemin d’accès souhaité. En outre, un générateur de chemin d’accès est proposé. Le résultant de la stratégie du contrôle donne une convergence globale du chemin actuel du MVA au chemin d’accès souhaité. Dans la deuxième partie, un contrôle en fonction de Lyapunov à l’aide de la théorie de la perturbation du singulier est proposé et appliqué sur la dynamique du MVA. En effet, dans cette partie on a abordé le problème diagnostic et la détection de pannes fault detection and diagnosis (FDD) pour un quadrirotor. Dans la troisième partie une nouvelle stratégie de contrôle pour effectuer la transition d’un avion convertible entre le mode avion et le mode hélicoptère, et vice versa, est présenté. L’analyse est effectuée pour le modèle longitudinal du PVHAT (Planar Vertical Helicopter-Airplane Transition) aéronef, lequel est un avion ayant disques pendulaires afin de réaliser la manœuvre de transition. L’algorithme de contrôle de boucle fermée qui en résulte, est prouvé être globalement asymptotiquement stable. Finalement, dans la quatrième partie de cette thèse, le problème de l’estimation et suivi d’un chemin à l’aide de vision système embarqué dans l’avion PVHAT est résolu. La stabilité globale exponentielle de la position sous-système ainsi que le contrôleur de commutation est démontrée. Des simulations illustratives et résultats expérimentaux sont obtenus sur plusieurs plateformes expérimentales développées dans cette thèse, pour évaluer l’applicabilité des principes contrôle proposés et mettre en valeur les mérites de l’approche. / This thesis studies some of the most relevant problems in the sense of guidance,navigation and control presented in a particular class of mini aerial vehicles (MAV) : the convertible MAV with fixed wings and tilting rotors. This aircraft is able to change its flight configuration from hover to level flight and vice-versaby means of a transition maneuver. Motivated by civilian applications, we theoretically and experimentally study Lyapunov-based control laws for dynamics presented in the convertible MAV. Results of asymptotic convergence are obtained over the complete flight envelope of the vehicle : from low-speed vertical flight through high-speed forward flight. We have divided this thesis in four main parts : the study of 1) the fixed-wingaircraft; 2) the quadrotor; 3) the convertible aircraft and 4) vision applications by using the convertible aircraft. In a first part, a Lyapunov-based controllaw is developed to steer a fixed wing mini aerial vehicle along a desired path. Furthermore a path generator is proposed. The resulting control strategy yields global convergence of the current path of the MAV to the desired path. In a second part, a Lyapunov-based control using singular perturbation theory is proposed and applied on dynamics of the MAV. Furthermore, in this part we address the problem of fault detection and diagnosis (FDD) for a quad-rotor. In the third part a new control strategy for the transition between airplane and helicopter mode, and vice versa, in convertible planes is presented. The analysis is carried out for the longitudinal model of the PVHAT (Planar VerticalHelicopter-Airplane Transition) aircraft, which is an airplane having tilting rotors in order to achieve the transition maneuver. The resulting closed loop control algorithm is proved to be globally asymptotically stable. Finally in thefourth part of this thesis the problem of estimation and tracking of a road using avision embedded system in the PVHAT aircraft is solved. The global exponential stability of the position subsystem together with the switching controller is demonstrated. Illustrative simulations and experimental results obtained on several experimental platforms developed in this thesis, assess the implementability of the proposed control laws and highlight the merits of the approach.

In this dissertation, we discuss the Distributed Spacecraft Attitude Control System Simulator (DSACSS) testbed developed at Virginia Polytechnic Institute and State University for the purpose of investigating various control techniques for single and multiple spacecraft. DSACSS is comprised of two independent hardware-in-the-loop simulators and one software spacecraft simulator. The two hardware-in-the-loop spacecraft simulators have similar subsystems as flight-ready spacecraft (e.g. command and data handling; communications; attitude determination and control; power; payload; and guidance and navigation). The DSACSS framework is a flexible testbed for investigating a variety of spacecraft control techniques, especially control scenarios involving coupled attitude and orbital motion. The attitude hardware simulators along with numerical simulations assist in the development and evaluation of Lyapunov based asymptotically stable, nonlinear attitude controllers with three reaction wheels as the control device. The angular rate controller successfully tracks a time varying attitude trajectory. The Modified Rodrigues Parmater (MRP) attitude controller results in successfully tracking the angular rates and MRP attitude vector for a time-varying attitude trajectory. The attitude controllers successfully track the reference attitude in real-time with hardware similar to flight-ready spacecraft. Numerical simulations and the attitude hardware simulators assist in the development and evaluation of a robust, asymptotically stable, nonlinear attitude controller with three reaction wheels as the actuator for attitude control. The MRPs are chosen to represent the attitude in the development of the controller. The robust spacecraft attitude controller successfully tracks a time-varying reference attitude trajectory while bounding system uncertainties. The results of a Global Positioning System (GPS) hardware-in-the-loop simulation of two spacecraft flying in formation are presented. The simulations involve a chief spacecraft in a low Earth orbit (LEO), while a deputy spacecraft maintains an orbit position relative to the chief spacecraft. In order to maintain the formation an orbit correction maneuver (OCM) for the deputy spacecraft is required. The control of the OCM is accomplished using a classical orbital element (COE) feedback controller and simulating continual impulsive thrusting for the deputy spacecraft. The COE controller requires the relative position of the six orbital elements. The deputy communicates with the chief spacecraft to obtain the current orbit position of the chief spacecraft, which is determined by a numerical orbit propagator. The position of the deputy spacecraft is determined from a GPS receiver that is connected to a GPS hardware-in-the-loop simulator. The GPS simulator creates a radio frequency (RF) signal based on a simulated trajectory, which results in the GPS receiver calculating the navigation solution for the simulated trajectory. From the relative positions of the spacecraft the COE controller calculates the OCM for the deputy spacecraft. The formation flying simulation successfully demonstrates the closed-loop hardware-in-the-loop GPS simulator. This dissertation focuses on the development of the DSACSS facility including the development and implementation of a closed-loop GPS simulator and evaluation of nonlinear feedback attitude and orbit control laws using real-time hardware-in-the-loop simulators. / Ph. D.