L'objectif de cette thèse est de définir puis d'étudier les performances de méthodes de guidage coopératif de véhicules aériens autonomes. L'intérêt du guidage coopératif est de confier une mission complexe à une flotte, plutôt qu'à un véhicule unique, afin de distribuer la charge de travail et d'améliorer les performances et la fiabilité. Les lois de guidage étudiées sont distribuées sur l'ensemble des véhicules afin d'une part, de répartir la charge de calcul et d'autre part, d'augmenter la fiabilité en éliminant la possibilité de perte de l'organe central de calcul de la commande.La première partie de la thèse porte sur les possibilités offertes par la règle des plus proches voisins. La loi de guidage développée consiste à ce que la commande de chaque véhicule soit élaborée en combinant les états des véhicules voisins. Afin de transmettre des consignes au groupe de véhicules, des objets dénommés agents virtuels sont introduits. Ceux-ci permettent de représenter des obstacles, d'indiquer une direction ou une cible au groupe de véhicules en utilisant des mécanismes déjà présent dans la loi de guidage.La seconde partie de la thèse porte sur les possibilités offertes par la commande prédictive. Ce type de commande consiste à employer un modèle du comportement du système afin de prédire les effets de la commande, et ainsi de déterminer celle qui minimise un critère de coût en respectant les contraintes du système. La loi de guidage développée emploi un critère de coût tenant compte et arbitrant entre les différents aspects de la mission (sécurité, progression de la mission, modération de la commande), et une procédure de recherche de la commande utilisant jeu prédéfinis de commandes candidates afin d'explorer l'espace de commande de manière efficace. Cette procédure, distincte des algorithmes d'optimisation habituels, génère une charge de calcul faible et constante, ne nécessite pas d'étape d'initialisation et est très peu sensible aux minima locaux. / The thesis objective is to define and study the performances of cooperative guidance methods of autonomous aerial vehicles. The interest of cooperative guidance is to entrust a complex mission to a fleet, instead of an isolated vehicle, to distribute the workload and improve performances and reliability. Studied guidance laws are distributed among all vehicles, on one hand to distribute the computation load, and on the other hand to remove the possibility to lose the centralized organ of command computation.The first part deals with the possibilities offered by the nearest neighbour rule. The developed guidance law consists in elaborating the command of each vehicle by combining the states of neighbour vehicles. To transmit instructions to the fleet of vehicles, objects denominated virtual agents are introduced. These allow figuring obstacles, indicating direction or target using existing mechanisms of the guidance law.The second part deals with the possibilities offered by model predictive control. This type of command consists in employing a behavioural model of the system to predict the control effects, and thus finding the one that minimises a cost criterion while respecting system's constraints. The developed guidance law uses a cost criterion that take into account and arbitrate between the several aspects of the mission (safety, mission evolution, control moderation), and a control search procedure based on a predefined set of candidate controls to explore the control space efficiently. This procedure, different from usual optimisation algorithms, generate a low and constant computation load, needs no initialisation step and is little sensitive to local minima.

Autonomous aerial vehicles like missiles and unmanned aerial vehicles (UAVs) have attracted various military and civilian applications. The primary guidance objective of any autonomous vehicle is to reach the desired destination point (target or waypoint). However, many practical engagements impose additional constraints like minimum control effort, a desired final velocity direction or a predefined engagement time. This thesis addresses engagement time constrained guidance problems pertaining to missiles and UAVs. The first part of the thesis discusses a nonlinear guidance law for impact time control of missiles against stationary target. The guidance law is designed with a particular choice of missile heading error variation as a function of ran to-target. The proposed heading error variation leads to an exact closed-form expression for the impact time. controlling the impact time, a closed-form relation is derived relating the control parameter to the desired impact time. A new Lyapunov based guidance law with a monotonically decreasing lateral acceleration is proposed in the next part of the thesis. An exact expression for impact time with minimum and maximum achievable impact times is derived. A control parameter is proposed with a closed-form relationship to the desired impact time. Using the concept of predicted interception point, the two guidance laws are extended for impact time control against non-maneuvering and moving targets. The proposed guidance models are extended to three-dimensional engagements by deducing yaw and pitch lateral accelerations satisfying the desired heading error profile. Extensive simulation studies are carried out for single missile and salvo attack scenarios. The last part of the thesis presents a guidance methodology governing the arrival time of a UAV at a waypoint. A specific arrival angle is considered as an additional constraint. The arrival constraints are satisfied by varying the navigation gain of the proportional navigation guidance law. The methodology is applied for simultaneous and sequential arrival of UAVs at a waypoint.