The general problem of multi-agent persistent monitoring finds applications in a variety of domains ranging from meter to kilometer-scale systems, such as surveillance or environmental monitoring, down to nano-scale systems such as tracking biological macromolecules for studying basic biology and disease. The problem can be cast as moving the agents between targets, acquiring information from or in some fashion controlling the states of the targets. Under this formulation, at least two questions need to be addressed. The first is the design of motion trajectories for the agents as they move among the spatially distributed targets and jointly optimize a given cost function that describes some desired application. The second is the design of the controller that an agent will use at a target to steer the target's state as desired. The first question can be viewed in at least two ways: first, as an optimal control problem with the domain of the targets described as a continuous space, and second as a discrete scheduling task. In this work we focus on the second approach, which formulates the target dynamics as a hybrid automaton, and the geometry of the targets as a graph. We show how to find solutions by translating the scheduling problem into a search for the optimal route. With a route specifying the visiting sequence in place, we derive the optimal time the agent spends at each target analytically. The second question, namely that of steering the target's state, can be formulated from the perspective of the target, rather than the agent. The mobile nature of the agents leads to intermittencontrol, such that the controller is assumed to be disconnected when no agent is at the target. The design of the visiting schedule of agents to one target can affect the reachability (controllability) of this target's control system and the design of any specific controller. Existing test techniques for reachability are combined with the idea of lifting to provide conditions on systems such that reachability is maintained in the presence of periodic disconnections from the controller. While considering an intermittently connected control with constraints on the control authority and in the presence of a disturbance, the concept of 'degree of controllability' is introduced. The degree is measured by a region of states that can be brought back to the origin in a given finite time. The size of this region is estimated to evaluate the performance of a given sequence.

L'objectif principal de ce travail de recherche est de contrôler l'évolution de la distribution des tailles de cristaux (DTC) dans un procédé de cristallisation en batch. Nous avons été amenés à chercher une résolution numérique du bilan de population et à proposer un algorithme rapide et précis. La méthode numérique a été étendue au cas de la taille des cristaux multidimensionnels en utilisant un maillage mouvant. Nous avons étudié le problème de la commandabilité du système à partir de son modèle discrétisé et puis à partir du modèle continu. Nous avons conçu une loi de commande en boucle fermée pour atteindre la DTC désirée à partir de la condition initiale. Pour compenser l'incertitude des paramètres du modèle, nous avons ajouté un second contrôle par retour d'état afin d'assurer la poursuite de la DTC désirée en présence de l'incertitude des paramètres. Nous avons construit un observateur qui nous permet d'avoir en ligne l'estimation des variables d'états. Ces variables d'état estimées sont utilisées dans la synthèse de la loi du contrôle / The main objective of this research is to control the evolution of the Crystal Size Distribution (CSD) in a batch crystallization process. We are led to study a numerical resolution of the population balance and propose an algorithm for fast and accurate simulation. This method was extended to the case of the two-dimensional crystal by using a moving mesh. We studied the problem of controllability of the system from its discretized model and then from the continuous model. To compensate the uncertainty of the model parameters, we added the second state feedback control to ensure the tracking of the desired CSD in presence of parameter uncertainty. We constructed an observer who provides us with on-line estimation of state variables. These state variables estimated are used in the control law synthesis