The presented research concerns the control of unmanned vehicles. The results introduced in this dissertation provide a solid control framework for a wide class of nonlinear uncertain systems, with a special emphasis on issues related to implementation, such as control input amplitude and rate saturation, or partial state measurements availability. More specifically, an adaptive control framework, allowing to enforce amplitude and rate saturation of the command, is developed. The motion control component of this framework, which works in conjunction with a saturation algorithm, is then specialized to different types of vehicles. Vertical take-off and landing aerial vehicles and a general class of autonomous marine vehicles are considered. A nonlinear control algorithm addressing the tracking problem for a class of underactuated, non-minimum phase marine vehicles is then introduced. This motion controller is extended, using direct and indirect adaptive techniques, to handle parametric uncertainties in the system model. Numerical simulations are used to illustrate the efficacy of the algorithms. Next, the output feedback control problem is treated, for a large class of nonlinear and uncertain systems. The proposed solution relies on a novel nonlinear observer which uses output measurements and partial knowledge of the system's dynamics to reconstruct the entire state for a wide class of nonlinear systems. The observer is then extended to operate in conjunction with a full state feedback control law and solve both the output feedback control problem and the state observation problem simultaneously. The resulting output feedback control algorithm is then adjusted to provide a high level of robustness to both parametric and structural model uncertainties. Finally, in a natural extension of these results from motion control of a single system to collaborative control of a group of vehicles, a cooperative control framework addressing limited communication issues is introduced. / Ph. D.

978-91-7729-579-2A multi-agent system consists of multiple agents cooperating to achieve a common objective through local interactions. An important problem is how to reduce the amount of information exchanged, since agents in practice only have limited energy and communication resources. In this thesis, we propose dynamic event-triggered control strategies to solve consensus and formation problems for multi-agent systems under such resource constraints. In the first part, we propose dynamic event-triggered control strategies to solve the average consensus problem for first-order continuous-time multi-agent systems. It is proven that the state of each agent converges exponentially to the average of all agents' initial states under the proposed triggering laws if and only if the underlying undirected graph is connected.In the second part, we study the consensus problem with input saturation over directed graphs. It is shown that the underlying directed graph having a directed spanning tree is a necessary and sufficient condition for achieving consensus. Moreover, in order to reduce the overall need of communication and system updates, we propose an event-triggered control strategy to solve this problem. It is shown that consensus is achieved, again, if and only if the underlying directed graph has a directed spanning tree.In the third part, dynamic event-triggered formation control with connectivity preservation is investigated. Single and double integrator dynamics are considered. All agents are shown to converge to the formation exponentially with connectivity preservation.The effectiveness of the theoretical results in the thesis is verified by several numerical examples. / <p>QC 20171025</p>

Cette thèse est consacrée au développement de techniques de commande avancées pour des classes de systèmes non linéaires en général et pour des applications automobiles en particulier.Pour répondre au besoin du contrôle moteur, la première partie propose des nouveaux résultats théoriques sur la technique de commande non linéaire à base de modèles de type Takagi-Sugeno soumis à la saturation de la commande. La saturation de la commande est traitée en utilisant sa représentation polytopique ou une stratégie anti-windup.La deuxième partie porte sur la commande du système d'air d'un moteur turbocompressé à allumage commandé. Deux approches originales sont proposées. Dans la première, l'outil théorique concernant les modèles Takagi-Sugeno à commutation développé dans la première partie est directement appliqué. La seconde approche est basée sur une commande linéarisante robuste. L'originalité de ces approches multivariables consiste dans sa simplicité de mise en œuvre et son efficacité par rapport à celles qui existent dans la littérature.La dernière partie vise à développer des stratégies pour la gestion énergétique des systèmes électriques d'un véhicule obtenues en se basant sur le Principe du Minimum de Pontryagin. À cet effet, deux approches sont considérées : l'approche hors ligne d'optimisation utilisant les informations du futur concernant les conditions de roulage et l'approche en ligne qui est adaptée de la précédente. Ensuite, ces deux approches sont implémentées et évaluées dans un simulateur avancé. / This thesis addresses the development of some advanced control design tools for a class of nonlinear systems in general and for automotive systems in particular.Motivated by automotive applications, Part I proposes some novel theoretical results on control design for nonlinear systems under Takagi-Sugeno form subject to the control input saturation. The input saturation is dealt with by using its polytopic representation or an anti-windup strategy.Part II deals with our automotive application concerning the control of a turbocharged air system of a spark ignition engine. To this end, two novel control approaches are proposed in this part. For the first one, the theoretical design tool on switching Takagi-Sugeno controller developed in Part I is directly applied. The second one is based on a robust feedback linearization control technique. The originality of these MIMO approaches consist in their simplicity and effectiveness compared to other ones existing in the literature.Part III aims at developing the strategies, which are based on the Pontryagin's Minimum Principle in optimal control theory, for the energy management of the vehicular electric power systems in a hybrid engine configuration. To this end, both offline optimization approach using the future information of driving conditions and online implementable one have been developed and evaluated in an advanced simulator.