A method is proposed to infer stability properties for non-linear switching under continuous state feedback. Continuous-time systems which are dissipative in the multiple storage function sense are considered. A partition of the state space, induced by the cross-supply rates and the feedback function, is used to derive a restriction on switching. Then, conditions are proposed, under which, systems controlled by the feedback function and switching according to the rule are stable. In particular, Lyapunov and asymptotic stability are proved, both in a local and in a global context. Further, it is shown that the approach can be extended when one uses multiple controllers, and, therefore, is able to construct multiple partitions; conditions for this case are also presented. Finally, it is shown that, for the switching families that satisfy the switching rule posited by the results, one is able to find elements (that is, stabilising switching laws for the system) which are non-Zeno. Additional rule-sets that allow this are provided. It is argued that the conditions proposed here are easier to verify and apply, and that they offer additional flexibility when compared to those proposed by other approaches in the literature. The same infrastructure is used in the study of hybrid systems. For a general class of non-linear hybrid systems, a new property is proposed, that retains some of the properties of dissipativity, but it differs from it, crucially in the fact that it is not purely input-output. For systems having this property, it is shown that the partition used in the switching case can also be used. This, along with a set of conditions allows for the characterisation of the system behaviour in two scenaria. First, when the continuous behaviours and the jumping scheme act co-operatively, leading the system to lower energy levels (from the dissipativity point of view). Second, when the continuous behaviours are allowed to increase the stored energy, but the jumping is able to 6 compensate this increase. In the first case, it is shown that the equilibrium point under study is stable; in the second, it is shown that the system exhibits a type of attractivity, and, under additional conditions, it is asymptotically stable. Besides stability, a collection of stabilisation results are given for the case of dissipative switching systems. It is shown that one may design state feedback functions (controllers) with the objective that they satisfy the conditions of the stability theorems in this work. Then, systems under the designed controllers are shown to be stable, provided that the switching adheres to a specific switching rule. This problem is approached using a variety of tools taken from analysis, multi-valued functions and the space of non-switching stabilisation. In addition to the main results, an extensive overview of the literature in the area of switching and hybrid systems is offered, with emphasis on the topics of stability and dissipativity. Finally, a collection of numerical examples are given, validating the results presented here.

The theory of impulsive dynamical systems is an important tool to describe the evolution of systems where the continuous development of a process is interrupted by abrupt changes of state. This phenomenon is called impulse. In many natural phenomena, the real deterministic models are often described by systems which involve impulses. The aim of this work is to investigate topological properties of impulsive semidynamical systems. We establish necessary and sufficient conditions to obtain uniform and orbital stability via Lyapunov functions. We solve a problem of Jake Hale for impulsive systems where we obtain the existence of a maximal compact invariant set. Also, we obtain results about almost periodic motions and asymptotically almost periodic motions in the context of impulsive systems. Some asymptotic properties for impulsive systems and for their associated discrete systems are investigated. The new results presented in this text are in the papers [11], [15] and [16]. / A teoria de sistemas dinâmicos com impulsos é apropriada para descrever processos de evolução que sofrem variações de estado de curta duração e que podem ser consideradas instantâneas. Este fenômeno é chamado impulso. Para muitos fenômenos naturais, os modelos determinísticos mais realistas são frequentemente descritos por sistemas que envolvem impulsos. O objetivo deste trabalho é estudar propriedades topológicas para sistemas semidinâmicos impulsivos. Estabelecemos condições necessárias e suficientes para obtermos estabilidade uniforme e estabilidade orbital utilizando funções do tipo Lyapunov. Resolvemos um problema de Jack Hale para os sistemas impulsivos, onde obtemos a existência de um conjunto invariante compacto maximal. Além disso, obtemos resultados de movimentos quase periódicos e movimentos assintoticamente quase periódicos para sistemas impulsivos. Algumas propriedades assintóticas são estabelecidas para um sistema impulsivo e para seu sistema discreto associado. Os resultados novos apresentados neste trabalho estão presentes nos artigos [11], [15] e [16].

The theory of impulsive dynamical systems is an important tool to describe the evolution of systems where the continuous development of a process is interrupted by abrupt changes of state. This phenomenon is called impulse. In many natural phenomena, the real deterministic models are often described by systems which involve impulses. The aim of this work is to investigate topological properties of impulsive semidynamical systems. We establish necessary and sufficient conditions to obtain uniform and orbital stability via Lyapunov functions. We solve a problem of Jake Hale for impulsive systems where we obtain the existence of a maximal compact invariant set. Also, we obtain results about almost periodic motions and asymptotically almost periodic motions in the context of impulsive systems. Some asymptotic properties for impulsive systems and for their associated discrete systems are investigated. The new results presented in this text are in the papers [11], [15] and [16]. / A teoria de sistemas dinâmicos com impulsos é apropriada para descrever processos de evolução que sofrem variações de estado de curta duração e que podem ser consideradas instantâneas. Este fenômeno é chamado impulso. Para muitos fenômenos naturais, os modelos determinísticos mais realistas são frequentemente descritos por sistemas que envolvem impulsos. O objetivo deste trabalho é estudar propriedades topológicas para sistemas semidinâmicos impulsivos. Estabelecemos condições necessárias e suficientes para obtermos estabilidade uniforme e estabilidade orbital utilizando funções do tipo Lyapunov. Resolvemos um problema de Jack Hale para os sistemas impulsivos, onde obtemos a existência de um conjunto invariante compacto maximal. Além disso, obtemos resultados de movimentos quase periódicos e movimentos assintoticamente quase periódicos para sistemas impulsivos. Algumas propriedades assintóticas são estabelecidas para um sistema impulsivo e para seu sistema discreto associado. Os resultados novos apresentados neste trabalho estão presentes nos artigos [11], [15] e [16].

Discontinuous dynamical systems and multiagent systems are encountered in numerous engineering applications. This dissertation develops stability and dissipativity of nonlinear dynamical systems with discontinuous right-hand sides, optimality of discontinuous feed-back controllers for Filippov dynamical systems, almost consensus protocols for multiagent systems with innaccurate sensor measurements, and adaptive estimation algorithms using multiagent network identifiers. In particular, we present stability results for discontinuous dynamical systems using nonsmooth Lyapunov theory. Then, we develop a constructive feedback control law for discontinuous dynamical systems based on the existence of a nonsmooth control Lyapunov function de fined in the sense of generalized Clarke gradients and set-valued Lie derivatives. Furthermore, we develop dissipativity notions and extended Kalman-Yakubovich-Popov conditions and apply these results to develop feedback interconnection stability results for discontinuous systems. In addition, we derive guaranteed gain, sector, and disk margins for nonlinear optimal and inverse optimal discontinuous feedback regulators that minimize a nonlinear-nonquadratic performance functional for Filippov dynamical systems. Then, we provide connections between dissipativity and optimality of nonlinear discontinuous controllers for Filippov dynamical systems. Furthermore, we address the consensus problem for a group of agent robots with uncertain interagent measurement data, and show that the agents reach an almost consensus state and converge to a set centered at the centroid of agents initial locations. Finally, we develop an adaptive estimation framework predicated on multiagent network identifiers with undirected and directed graph topologies that identifies the system state and plant parameters online.

"Maintaining an efficient and reliable infrastructure requires continuous monitoring and control. In order to accomplish these tasks, algorithms are needed to process large sets of data and for modeling based on these processed data sets. For this reason, computationally efficient and accurate modeling algorithms along with data compression techniques and optimal yet practical control methods are in demand. These tools can help model structures and improve their performance. In this thesis, these two aspects are addressed separately. A principal component analysis based adaptive neuro-fuzzy inference system is proposed for fast and accurate modeling of time-dependent behavior of a structure integrated with a smart damper. Since a smart damper can only dissipate energy from structures, a challenge is to evaluate the dissipativity of optimal control methods for smart dampers to decide if the optimal controller can be realized using the smart damper. Therefore, a generalized deterministic definition for dissipativity is proposed and a commonly used controller, LQR is proved to be dissipative. Examples are provided to illustrate the effectiveness of the proposed modeling algorithm and evaluating the dissipativity of LQR control method. These examples illustrate the effectiveness of the proposed modeling algorithm and dissipativity of LQR controller."

Le transport a toujours été l'un des composants déterminants de la vie urbaine et de son développement économique. A partir de la seconde moitié du siècle dernier, l'amélioration du niveau de vie moyen et du taux d'équipement des ménages a permis au plus grand nombre d'accéder au déplacement par véhicule particulier. Nous avons donc assisté à une course entre la croissance du trafic routier et les progrès quantitatifs et qualitatifs de la voirie. Cette quantité d'actions génère des problèmes au niveau de la fluidité du trafic, d'où l'apparition de congestion.La congestion se produit aujourd'hui de façon quasi-quotidienne dans les réseaux routiers. Elle est source de perte de temps, augmentation de la consommation d'énergie, nuisance et détérioration de l'environnement. La solution aux problèmes de congestion routière ne passe pas toujours par l'augmentation de l'investissement dans les infrastructures de transport. En effet, l'offre de terrains est épuisée et le développement de l'infrastructure routière est coûteux. D'où, la tendance actuelle est plutôt à une meilleure utilisation des infrastructures existantes. En particulier, les feux de signalisation jouent un rôle important parmi les approches qui permettent d'éviter la congestion. En effet, la conception d'une meilleur commande des feux de signalisation a fait l'objet de plusieurs recherches afin d’améliorer la circulation au niveau du réseau à grande échelle.Dans ce mémoire, nous nous intéressons essentiellement à un travail en amont (action a priori) permettant d'éviter la congestion en forçant le nombre de véhicules à ne pas dépasser les capacités maximales des voies du réseau de transport. Après avoir décrire les réseaux de carrefours des feux, nous présentons d'une manière non exhaustive, les méthodes développées pour la gestion et la régulation des carrefours. Ensuite, nous proposons trois stratégies de contrôle qui traitent le problème de contrôle de manières différentes. La première fait appel à la théorie des systèmes dissipatifs, la deuxième consiste à stabiliser le système au sens de Lyapunov autour de sa situation nominale et la troisième le stabilise en temps fini (pendant les heures de pointe). Ces commandes proposées respectent les contraintes sur l'état et sur la commande et prennent en considération les incertitudes existantes dans le système. Finalement, l'existence des commandes proposées a été caractérisée par la faisabilité de certaines LMI en utilisant l'outil CVX sous MATLAB. De plus, les performances de chaque commande sont évaluées par des simulations. / Transport has always been one of the key components of urban life and its economic development. From the second half of the last century, the improvement in the average standard of living and the household equipment rate allowed the greatest number of people to access the journey by private vehicle. We therefore witnessed a race between the growth of road traffic and the quantitative and qualitative progress of roads. This quantity of actions generates problems with the fluidity of the traffic, hence the appearance of congestion.The congestion occurs today almost daily in road networks. It is source of waste of time, increase of the energy consumption, the nuisance and the deterioration of the environment. The solution to the problems of road congestion does not still pass by the increase of the investment in the infrastructures of transport. Indeed, the offer of grounds is exhausted and the development of the road infrastructure is expensive. Hence, the current trend is rather for a better use of the existing infrastructures. In particular, traffic lights play an important role in avoiding congestion. Indeed, the design of a better control of traffic lights has been the subject of several researches in order to improve the network circulation on a large scale.In this thesis, we are mainly interested in a work that prevents the congestion by forcing the number of vehicles to not exceed the lane capacities. After having described the network of intersections, we have realized a state of the art on the methods developed for the management and regulation of intersections. Next, we propose three control strategies that treat the control problem in different ways. The first one involves the theory of dissipative systems, the second one is to stabilize the system in the sense of Lyapunov around its nominal situation and the third one stabilizes it in finite time (during peak hours). These proposed controls respect the constraints on both state and control. In addition, they take into account the uncertainties in the system. Finally, the result of each strategy developed is presented by LMI in order to be solved by using the CVX tool under MATLAB. Besides, the performance of each control is evaluated by simulations.

Dans cette thèse, on étudie l'existence, l'unicité et la régularité des solutionsd'équation de type Cahn-Hilliard ainsi que son comportement asymptotiqueen termes d'existence de l'attracteur global et d'un attracteur exponentiel. Cetteéquation est considérée dans un domaine borné et régulier pour différents types denonlinéarités et de conditions au bord.D'abord, on étudie l'équation avec des conditions de type Dirichlet sur le bord etune nonlinéarité régulière. Après, on considère une perturbation du problème et ondémontre l'existence d'une famille robuste d'attracteurs exponentiels lorsque ε tendvers 0.Ensuite, on étudie l'équation avec des conditions dynamiques sur le bord. On considèretout d'abord une nonlinéarité régulière et on donne une étude théorique etnumérique. Après, on illustre ces résultats par des simulations numériques en dimensiondeux d'espace qui permettent d'étudier l'influence des différents paramètres.On termine par une étude du modèle considéré avec une nonlinéarité singulière quel'on approche par des fonctions régulières et on introduit une notion de solutionappropriée. / This thesis is devoted to the study of the existence, uniqueness andregularity of solutions for a Cahn-Hilliard type equation, as well as the asymptoticbehavior in terms of existence of the global attractor and of an exponential attractor.This equation is considered in a bounded and smooth domain under variousassumptions on the nonlinear terms and with different boundary conditions.We start by studying the equation with Dirichlet boundary conditions and a regularnonlinearity. Then, we consider a perturbation of the problem and we prove theexistence of a robust family of exponential attractors as ε tends to 0.For the equation endowed with dynamic boundary conditions, we first consider aregular nonlinearity and we treat the theoretical and numerical analysis. Then, weillustrate the results by numerical simulations in two space dimension which allow usto study the influence of different parameters. Finally, we treat the problem consideredwith a singular nonlinearity which is approximated by regular functions andwe give a suitable notion of solutions.

The study of non-linear input-output maps can be summarized by three concepts: Gain, Positivity and Dissipativity. However, in order to make efficient use of these theorems it is necessary to use loop transformations and weightings, or so called ”multipliers”.The first problem this thesis studies is the feedback interconnection of a Linear Time Invariant system with a memoryless bounded and monotone non-linearity, or so called Absolute Stability problem, for which the test for stability is equivalent to show the existence of a Zames-Falb multiplier. The main advantage of this approach is that Zames–Falb multipliers can be specialized to recover important tools such as Circle criterion and the Popov criterion. Albeit Zames-Falb multipliers are an efficient way of describing non-linearities in frequency domain, the Fourier transform of the multiplier does not preserve the L1 norm. This problem has been addressed by two paradigms: mathematically complex multipliers with exact L1 norm and multipliers with mathematically tractable frequency domain properties but approximate L1 norm. However, this thesis exposes a third factor that leads to conservative results: causality of Zames-Falb multipliers. This thesis exposes the consequences of narrowing the search Zames-Falb multipliers to causal multipliers, and motivated by this argument, introduces an anticausal complementary method for the causal multiplier synthesis in [1].The second subject of this thesis is the feedback interconnection of two bounded systems. The interconnection of two arbitrary systems has been a well understood problem from the point of view of Dissipativity and Passivity. Nonetheless, frequency domain analysis is largely restricted for passive systems by the need of canonically factorizable multipliers, while Dissipativity mostly exploits constant multipliers. This thesis uses IQC to show the stability of the feedback interconnection of two non-linear systems by introducing an equivalent representation of the IQC Theorem, and then studies formally the conditions that the IQC multipliers need. The result of this analysis is then compared with Passivity and Dissipativity by a series of corollaries.

Ces travaux de thèse concernent l'analyse de la robustesse (stabilité et performance) de systèmes linéaires incertains de grande dimension avec une structure hiérarchique. Ces systèmes sont obtenus en interconnectant plusieurs sous-systèmes incertains à travers une topologie hiérarchique. L'analyse de la robustesse de ces systèmes est un problème à deux aspects : la robustesse et la grande dimension. La résolution efficace de ce problème en utilisant les approches usuelles est difficile, voire impossible, à cause de la complexité et de la grande taille du problème d'optimisation associé. La conséquence de cette complexité est une augmentation importante du temps de calcul nécessaire pour résoudre ce problème d'optimisation. Afin de réduire ce temps de calcul, les travaux existants ne considèrent que des classes particulières de systèmes linéaires incertains de grande dimension. De plus, la structure hiérarchique de ces systèmes n'est pas prise en compte, ce qui montre, de notre point de vue, les limitations de ces résultats. Notre objectif est d'exploiter la structure hiérarchique de ces systèmes afin de ramener la résolution du problème d'analyse de grande taille à la résolution d'un ensemble de problèmes d'analyse de faible taille, ce qui aura comme conséquence une diminution du temps de calcul. De plus, un autre avantage de cette approche est la possibilité de résoudre ces problèmes en même temps en utilisant le calcul parallèle. Afin de prendre en compte la structure hiérarchique du système incertain de grande dimension, nous modélisons ce dernier comme l'interconnexion de plusieurs sous-systèmes incertains qui sont eux-mêmes l'interconnexion d'autres sous-systèmes incertains, etc.. Cette technique récursive de modélisation est faite sur plusieurs niveaux hiérarchiques. Afin de réduire la complexité de la représentation des systèmes incertains, nous construisons une base de propriétés de dissipativité pour chaque sous-système incertain de chaque niveau hiérarchique. Cette base contient plusieurs éléments qui caractérisent des informations utiles sur le comportement de systèmes incertains. Des exemples de telles caractérisations sont : la caractérisation de la phase incertaine, la caractérisation du gain incertain, etc.. L'obtention de chaque élément est relaxée comme un problème d'optimisation convexe ou quasi-convexe sous contraintes LMI. L'analyse de la robustesse de systèmes incertains de grande dimension est ensuite faite de façon hiérarchique en propageant ces bases de propriétés de dissipativité d'un niveau hiérarchique à un autre. Nous proposons deux algorithmes d'analyse hiérarchique qui permettent de réduire le temps de calcul nécessaire pour analyser la robustesse de ces systèmes. Un avantage important de notre approche est la possibilité d'exécuter des parties de ces algorithmes de façon parallèle à chaque niveau hiérarchique ce qui diminuera de façon importante ce temps de calcul. Pour finir et dans le même contexte de système de grande dimension, nous nous intéressons à l'analyse de la performance dans les réseaux électriques et plus particulièrement «l'analyse du flux de puissances incertaines dans les réseaux électriques de distribution». Les sources d'énergies renouvelables comme les éoliennes et les panneaux solaires sont influencées par plusieurs facteurs : le vent, l'ensoleillement, etc.. Les puissances générées par ces sources sont alors intermittentes, variables et difficiles à prévoir. L'intégration de telles sources de puissance dans les réseaux électriques influencera les performances en introduisant des incertitudes sur les différentes tensions du réseau. L'analyse de l'impact des incertitudes de puissances sur les tensions est appelée «analyse du flux de puissances incertaines». La détermination de bornes sur les modules des différentes tensions est formulée comme un problème d'optimisation convexe sous contraintes LMI. / This PhD thesis concerns robustness analysis (stability and performance) of uncertain large scale systems with hierarchical structure. These systems are obtained by interconnecting several uncertain sub-systems through a hierarchical topology. Robustness analysis of these systems is a two aspect problem: robustness and large scale. The efficient resolution of this problem using usual approaches is difficult, even impossible, due to the high complexity and the large size of the associated optimization problem. The consequence of this complexity is an important increase of the computation time required to solve this optimization problem. In order to reduce this computation time, the existing results in the literature focus on particular classes of uncertain linear large scale systems. Furthermore, the hierarchical structure of the large scale system is not taken into account, which means, from our point of view, that these results have several limitations on different levels. Our objective is to exploit the hierarchical structure to obtain a set of small scale size optimization problems instead of one large scale optimization problem which will result in an important decrease in the computation time. Furthermore, another advantage of this approach is the possibility of solving these small scale optimization problems in the same time using parallel computing. In order to take into account the hierarchical structure, we model the uncertain large scale system as the interconnection of uncertain sub-systems which themselves are the interconnection of other uncertain sub-systems, etc.. This recursive modelling is performed at several hierarchical levels. In order to reduce the representation complexity of uncertain systems, we construct a basis of dissipativity properties for each uncertain sub-system at each hierarchical level. This basis contains several elements which characterize different useful information about uncertain system behaviour. Examples of such characterizations are: uncertain phase characterization, uncertain gain characterization, etc.. Obtaining each of these elements is relaxed as convex or quasi-convex optimization problem under LMI constraints. Robustness analysis of uncertain large scale systems is then performed in a hierarchical way by propagating these dissipativity property bases from one hierarchical level to another. We propose two hierarchical analysis algorithms which allow to reduce the computation time required to perform the robustness analysis of the large scale systems. Another key point of these algorithms is the possibility to be performed in parallel at each hierarchical level. The advantage of performing robustness analysis in parallel is an important decrease of the required computation time. Finally and within the same context of robustness analysis of uncertain large scale systems, we are interested in robustness analysis of power networks and more precisely in "the uncertain power flow analysis in distribution networks". The renewable energy resources such as solar panels and wind turbines are influenced by many factors: wind, solar irradiance, etc.. Therefore, the power generated by these resources is intermittent, variable and difficult to predict. The integration of such resources in power networks will influence the network performances by introducing uncertainties on the different network voltages. The analysis of the impact of power uncertainties on the voltages is called "uncertain power flow analysis". Obtaining the boundaries for the different modulus of these voltages is formulated as a convex optimization problem under LMI constraints

This thesis is concerned with large-scale systems of Ordinary Differential Equations that model Biomolecular Reaction Networks (BRNs) in Systems and Synthetic Biology. It addresses the strategies of model reduction and decomposition used to overcome the challenges posed by the high dimension and stiffness typical of these models. A number of developments of these strategies are identified, and their implementation on various BRN models is demonstrated. The goal of model reduction is to construct a simplified ODE system to closely approximate a large-scale system. The error estimation problem seeks to quantify the approximation error; this is an example of the trajectory comparison problem. The first part of this thesis applies semi-definite programming (SDP) and dissipativity theory to this problem, producing a single a priori upper bound on the difference between two models in the presence of parameter uncertainty and for a range of initial conditions, for which exhaustive simulation is impractical. The second part of this thesis is concerned with the BRN decomposition problem of expressing a network as an interconnection of subnetworks. A novel framework, called layered decomposition, is introduced and compared with established modular techniques. Fundamental properties of layered decompositions are investigated, providing basic criteria for choosing an appropriate layered decomposition. Further aspects of the layering framework are considered: we illustrate the relationship between decomposition and scale separation by constructing singularly perturbed BRN models using layered decomposition; and we reveal the inter-layer signal propagation structure by decomposing the steady state response to parametric perturbations. Finally, we consider the large-scale SDP problem, where large scale SDP techniques fail to certify a system’s dissipativity. We describe the framework of Structured Storage Functions (SSF), defined where systems admit a cascaded decomposition, and demonstrate a significant resulting speed-up of large-scale dissipativity problems, with applications to the trajectory comparison technique discussed above.