Avec le développement des véhicules électriques, la question de la valorisation des batteries lithium-ion (BLI) se pose pour diverses raisons. Pourtant, une filière de valorisation structurée n’existe pas aujourd’hui. Notre travail académique a pour objet l’étude de cette dernière. La filière de valorisation des BLIs est définie comme un système sociotechnique, complexe en émergence. Notre problématique consiste alors à l’étudier d’un point de vue technico-économique, organisationnel et prospectif et ce en tenant compte des différentes complexités. Cette problématique soulève trois questions de recherche : Comment modéliser la filière de valorisation des BLIs comme un système organisationnel complexe en émergence ? Comment faire de la prospective sur la filière de valorisation des BLIs ? Comment analyser la gouvernance de la filière de valorisation des BLIs ?Pour modéliser la filière de valorisation des BLIs, nous mettons en œuvre d’une manière combinée trois méthodes de modélisation systémiques : SCOS’M (Systemics for Complex Organisational Systems’ Modelling), la cartographie cognitive et la dynamique des systèmes. La modélisation a pour objectif la caractérisation de la filière (parties prenantes, sous-systèmes …), la compréhension de ses dynamiques d’évolution et l’identification des variables clés dans ces dynamiques. Cette modélisation est une base pour la suite.Pour faire de la prospective sur la filière de valorisation des BLIs, nous préconisons l’utilisation des scénarios. Ces derniers sont définis à l’aide de la matrice SRI (Stranford Research Institute), en exploitant les variables clés qui interviennent dans les dynamiques d’évolution de la filière. La prospective est permise en simulant le modèle dynamique des systèmes avec différents scénarios, afin d’analyser les aspects technico-économiques. Pour l’étude de la gouvernance de la filière de valorisation des BLIs, le périmètre a été restreint à l’activité de reconditionnement. Dans ce cas, l’étude de la gouvernance revient à analyser des combinaisons de répartition (application 2nde vie, partie prenante). Une méthodologie d’aide à la décision a été développée pour cette fin. D’une manière générale, cette thèse a identifié les enjeux et questions qui se posent lors de l’étude de la valorisation des batteries lithium-ion des véhicules électriques. A travers notre modélisation, nous avons établi une base d’analyse utile à l’aide à la décision. Nous avons répondu à certaines questions (aspects technico-économiques et organisationnels) et ouvert la voie pour d’autres (aspects logistiques et environnementaux). / With the development of electric vehicles, the recovery of lithium-ion batteries (LIB) arises for various reasons. However, a structured recovery network does not exist today. Our academic work aims to study this latter. The LIBs recovery network is defined as a socio-technical complex emerging system. Our problematic is then to study it from a technical-economic, organizational and prospective perspective, taking into account the different complexities. This problematic raises three research questions: How to model the LIBs recovery network as a complex organizational emerging system? How to foresight on the LIBs recovery network? How to analyze the LIBs recovery network governance?To model the LIBs recovery network, we apply with combination three systemic modeling methods: SCOS'M (Systemics for Complex Organisational Systems' Modelling), cognitive mapping and system dynamics. The modeling aims to characterize the recovery network (stakeholders, subsystems ...), understand its dynamics and identify the key variables in these dynamics. This model is the basis for the following research questions.To Foresight on the LIBs recovery network, we recommend the use of scenarios. These are defined using the SRI matrix (Stranford Research Institute), exploiting the key variables. Foresight is permitted by simulating the system dynamics model with different scenarios to analyze the technical-economic aspects. For the study of the LIBs recovery network governance, the scope was restricted to the repurposing activity. In this case, the study of the governance comes down to analyzing the combinations (2nd life application, stakeholder). A decision aid methodology has been developed for this purpose. In general, this thesis identified the questions that arise when considering the recovery of LIBs. Through our modeling, we have established a useful basis for decision aid. We answered some questions (technical-economic and organizational aspects) and paved the way for others (logistical and environmental aspects).

<div>Disaster debris management is critical to the success of disaster recovery systems. While there are multiple disaster mitigation strategies and post-disaster debris management plans, it is hard to implement because of: (i) the uniqueness of disaster incidents and randomness of its impacts; (ii) complexity of disaster debris removal operations, policy and regulations and (iii) interdependency of multiple infrastructure networks. Also, delayed debris removal operation affects following emergency response activities. Furthermore, uncontrolled debris removal activities can result in significant environmental and public health consequences. Therefore, there is a need for a systematic approach to optimizing post-disaster debris management systems. </div><div><br></div><div>This research is aimed to understand the complexity of debris management and associated emergent dynamics through the lens of an adaptive system-of-systems (SoS). To develop the adaptive decision support system, this research (a) identifies the interdependent infrastructure network within a community and its relative importance; (b) develops real-time GIS database to integrate the data associated with critical infrastructure and geographical characteristics in the community map; (c) designs and selects a TDMS network to analyze the required number, capacity and resources, based on engineering-technical, managerial, and social-political dynamics; (d) simulate the productivity of debris-management SoS based on the real-time GIS database to gain insight into the impact of the dynamical nature of a disaster-affected area; and (e) develop a visualized interactive GIS-based platform for debris management to communicate real-time debris clearance strategies and operations among different agencies and organizations.</div><div><br></div><div>To evaluate the proposed framework and decision support system, this research conducted a case study, debris removal operation in the city of Baton Rouge, after the 2016 Louisiana flood. The results demonstrated the influence of sub-systems such as TDMS locations and capacity, road network condition, available resources, existing regulations and policies, characteristics of community on the behavior of the entire disaster debris removal management as a whole. </div><div><br></div><div>The proposed decision support system for effective disaster debris management will be beneficial for emergency agencies and disaster-prone communities to evaluate and optimize their disaster debris management system. Also, the system can be systematically integrated with other emergency response systems to maximize the efficiency of the entire disaster responses during post-disaster situations. </div><div><br></div>

The rapid growth in additive manufacturing technologies have brought various optimization techniques and methodologies to improve each phase that needs to be integrated and analyzed on system level to optimize the system performance. The challenges and limitations of each phase affect the system when integrated as a whole - creating a complex manufacturing environment that needs to be critically examined and managed. To have a better management of complex, emergent, and uncertain manufacturing system from design to recycling phase, a new way of thinking based on more holistic approach is necessary. In this paper, the system of systems paradigm (SoS) is introduced to treat additive manufacturing system as a whole and to present some SoS approaches that are based on holistic thinking. This paper provides a conceptual knowledge of SoS approach using systems principles, laws and approach emphasizing the characteristics and attributes of complex manufacturing system to the AM domain.

Ce travail de thèse porte sur l'étude des systèmes complexes par une démarche de modélisation et simulation (M&S). La plupart des questionnements sur ces systèmes nécessitent de prendre en compte plusieurs points de vue simultanément. Il faut alors considérer des phénomènes évoluant à des échelles (temporelles et spatiales) et des niveaux de résolutions (de microscopique à macroscopique) différents. De plus, l'expertise nécessaire pour décrire le système vient en général de plusieurs domaines scientifiques. Les défis sont alors de concilier ces points de vues hétérogènes, et d'intégrer l'existant de chaque domaine (formalismes et logiciels de simulation) tout en restant dans le cadre rigoureux de la démarche de M&S. Pour répondre à ces défis, nous mobilisons à la fois des notions de modélisation multi-niveau (intégration de représentations micro/macro), de modélisation hybride (intégration de formalismes discrets/continus), de simulation parallèle, et d'ingénierie logicielle (interopérabilité logiciel, et ingénierie dirigée par les modèles). Nous nous inscrivons dans la continuité des travaux de M&S existants autour de l'approche AA4MM et du formalisme DEVS. Nous étudions en effet dans cette thèse en quoi ces approches sont complémentaires et permettent, une fois combinées dans une démarche d'Ingénierie Dirigée par les Modèles (IDM), de répondre aux défis de la M&S des systèmes complexes. Notre contribution est double. Nous proposons d'une part les spécifications opérationnelles de l'intergiciel de co-simulation MECSYCO permettant de simuler en parallèle un modèle de manière rigoureuse et complètement décentralisée. D'autre part, nous proposons une approche d'IDM permettant de décrire de manière non-ambiguë des modèles, puis de systématiser leur implémentation dans MECSYCO. Nous évaluons les propriétés de notre approche à travers plusieurs preuves de concept portant sur la M&S du trafic autoroutier et sur la résolution numérique d'un système d'équations différentielles / This thesis is focused on the study of complex systems through a modeling and simulation (M&S) process. Most questions about such systems requiere to take simultaneously account of several points of view. Phenomena evolving at different (temporal and spatial) scales and at different levels of resolution (from micro to macro) have to be considered. Moreover, several expert skills belonging to different scientific fields are needed. The challenges are then to reconcile these heterogeneous points of view, and to integrate each domain tools (formalisms and simulation software) within the rigorous framework of the M&S process. In order to solve these issues, we mobilise notions from multi-level modeling, hybrid modeling, parallel simulation and software engineering. Regarding these fields, we study the complementarity of the AA4MM approach and the DEVS formalism into the scope of the model-driven engineering (MDE) approach. Our contribution is twofold. We propose the operational specifications of the MECSYCO co-simulation middleware enabling the parallel simulation of complex systems models in a rigorous and decentralized way. We also define an MDE approach enabling the non-ambiguous description of complex systems models and their automatic implementation in MECSYCO. We show the properties of our approach with several proofs of concept

Gegenstand dieser Arbeit ist die Untersuchung generischer Synchronisierungsphänomene in interagierenden komplexen Systemen. Diese Phänomene werden u.a. in gekoppelten deterministischen chaotischen Systemen beobachtet. Bei sehr schwachen Interaktionen zwischen individuellen Systemen kann ein Übergang zum schwach kohärenten Verhalten der Systeme stattfinden. In gekoppelten zeitkontinuierlichen chaotischen Systemen manifestiert sich dieser Übergang durch den Effekt der Phasensynchronisierung, in gekoppelten chaotischen zeitdiskreten Systemen durch den Effekt eines nichtverschwindenden makroskopischen Feldes.<br /> Der Übergang zur Kohärenz in einer Kette lokal gekoppelter Oszillatoren, beschrieben durch Phasengleichungen, wird im Bezug auf die Symmetrien des Systems untersucht. Es wird gezeigt, daß die durch die Symmetrien verursachte Reversibilität des Systems nichttriviale topologische Eigenschaften der Trajektorien bedingt, so daß das als dissipativ konstruierte System in einem ganzen Parameterbereich quasi-Hamiltonische Züge aufweist, d.h. das Phasenvolumen ist im Schnitt erhalten, und die Lyapunov-Exponenten sind paarweise symmetrisch.<br /> Der Übergang zur Kohärenz in einem Ensemble global gekoppelter chaotischer Abbildungen wird durch den Verlust der Stabilität des entkoppelten Zustandes beschrieben. Die entwickelte Methode besteht darin, die Selbstkonsistenz des makroskopischen Feldes aufzuheben, und das Ensemble in Analogie mit einem Verstärkerschaltkreis mit Rückkopplung durch eine komplexe lineare Übertragungssfunktion zu charakterisieren.<br /> Diese Theorie wird anschließend für einige theoretisch interessanten Fälle verallgemeinert. / Subject of this work is the investigation of generic synchronization phenomena in interacting complex systems. These phenomena are observed, among all, in coupled deterministic chaotic systems. At very weak interactions between individual systems a transition to a weakly coherent behavior of the systems can take place. In coupled continuous time chaotic systems this transition manifests itself with the effect of phase synchronization, in coupled chaotic discrete time systems with the effect of non-vanishing macroscopic mean field.<br /> Transition to coherence in a chain of locally coupled oscillators described with phase equations is investigated with respect to the symmetries in the system. It is shown that the reversibility of the system caused by these symmetries results to non-trivial topological properties of trajectories so that the system constructed to be dissipative reveals in a whole parameter range quasi-Hamiltonian features, i.e. the phase volume is conserved on average and Lyapunov exponents come in symmetric pairs.<br /> Transition to coherence in an ensemble of globally coupled chaotic maps is described with the loss of stability of the disordered state. The method is to break the self-consistensy of the macroscopic field and to characterize the ensemble in analogy to an amplifier circuit with feedback with a complex linear transfer function.<br /> This theory is then generalized for several cases of theoretic interest.

The continuous progression of urbanization has resulted in an increasing number of people living in cities or towns. In parallel, advancements in technologies, such as the Internet, telecommunications, and transportation, have allowed for better connectivity among people. This has engendered drastic changes in urban systems during the recent decades. From a social geographic perspective, the changes in urban systems are primarily characterized by intensive contacts among people and their interactions with the surrounding urban environment, which further leads to subsequent challenging problems such as traffic jams, environmental pollution, urban sprawl, etc. These problems have been reported to be heterogeneous and non-deterministic. Hence, to cope with them, massive amounts of geographic data are required to create new knowledge on urban systems. Due to the thriving of Volunteer Geographic Information (VGI) in recent years, this thesis presents knowledge on urban systems based on extensive VGI datasets from three sources: highway dataset from the OpenStreetMap (OSM) project, photo location dataset from the Flickr website, and GPS tracking datasets from volunteers, taxicabs, and air flights. The knowledge primarily relates to two issues of urban systems: the urban space and the corresponding human dynamics. In accordance, on one hand, urban space acts as a carrier for associated geographic activities and knowledge of it benefits our understanding of current social and economic problems in urban systems. On the other hand, human dynamics reflect human behavior in urban space, which leads to complex mobility or activity patterns. Its investigation allows a derivation of the underlying driving force that is very instructive to urban planning, traffic management, and infectious disease control. Therefore, to fully understand the two issues, this thesis conducts a thorough investigation from multiple aspects. The first issue is investigated from four aspects. First, at the city level, the controversial topic of city size regularity is investigated in terms of natural cities, and the conclusion is that Zipf’s law holds stably for all US cities. Second, at the sub-city level, the size distribution of spatial units within different cities in terms of the clusters formed by street nodes, photo locations, and taxi static points are explored, and the result shows a remarkable scaling property of these spatial units. Third, enlightened by the scaling property of the urban space at the city or sub-city level, this thesis devises a novel tool that can demarcate the cities into three categories: compact cities, normal cities, and sprawling cities. The tool is then applied to cities in both the US and three European countries. In the last, another representation of urban space is taken into account, namely the transportation network. The findings report that the US airport network displays the properties of scale-free, small-world, and disassortative mixing and that the individual natural airports show heterogeneous patterns that are probably subject to geographic constraints and socioeconomic factors. The second issue is examined from four perspectives. First, at the city level, the movement flow contributed by agents using two types of behavior is investigated through an agent-based simulation, and the result conjectures that the human mobility behavior is mainly shaped by the underlying street network. Second, at the country level, this thesis reports that the human travel length by air can be approximated well by an exponential distribution, and subsequent simulations indicate that human mobility behavior is largely constrained by the underlying airport network. Third, at the regional level, the length that humans travel by car is demonstrated to agree well with a power law with exponential cutoff distribution, and subsequent simulation further reproduces this levy flight characteristic. Based on the simulation, human mobility behavior is again revealed to be primarily shaped by the underlying hierarchical spatial structure. Finally, taxicab static points are adopted to explore human activity patterns, which can be characterized as the regularities in space and time, the heterogeneity and predictability in space. From a complex system perspective, this thesis presents the knowledge discovered in urban systems using massive volumes of geographic data. Together with new knowledge from empirical findings, the development of methods, and the design of theoretic models, this thesis also shares the research community with geographic data generated from extensive VGI datasets and the corresponding source codes. Moreover, this study is aligned with a paradigm shift in that it analyzes large-size datasets using high processing power as opposed to analyzing small-size datasets with low processing power. / <p>QC 20121113</p>

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

Thema der Arbeit ist die Konzeption, Entwicklung und Einführung in die Anwendung eines Entwurfssystems, das die Leistungsfähigkeit der derzeit während des Entwurfsprozesses angewandten Programme durch neue Funktionen erweitert. Die implementierte integrative Schnittstellenlösung fasst die bisher genutzten Applikationen zu einem Gesamtsystem zusammen. Der bidirektionale Datenaustausch zwischen allen integrierten Modulen verhindert zur Zeit noch notwendige Mehrfacheingaben identischer Daten. Die für die Modellierung eingesetzten CAD-Systeme bieten für die rechnerinterne Abbildung der Geometrie von Bauteilen eine hohe Funktionalität. Ungenügend ist aber die Erstellung der Funktionsstruktur mit rechentechnischen Hilfsmitteln gelöst. Dieses führt zum Entwurf neuer Produkte nahezu ohne den Einsatz der Informationstechnik und zur anschließenden Anfertigung der CAD-Modelle und Zeichnungen, wenn die Bauteile bereits in ihrer Grundstruktur bestimmt sind. Auch die Vorteile der parametrischen 3D-Modellierung, die für die Beschreibung der bauteilinternen Abhängigkeiten anwendbar ist, werden nur begrenzt genutzt. Gründe dafür liegen in der komplizierten Definition eineindeutig bestimmter Modelle und im ungenügend gelösten Datenaustausch mit externen Applikationen. Während die Ergebnisse einer Konstruktion als rechnerinterne Geometriemodelle detailliert vorliegen, werden die Daten der zugrunde liegenden Funktionsstruktur nicht oder nur zum geringen Teil erfasst. Wichtige Informationen über den Entstehungsprozess sind somit nach Abschluss einer Konstruktion nicht mehr verfügbar. Aufgrund dessen muss die gleichwertige Modellierung von Funktions- und Wirkstruktur sowie der Geometrie realisiert werden. Mit dem beschriebenen Entwurfssystem werden diese Strukturen erstellt und in einem komplexen Modell gespeichert. Im Rahmen folgender Konstruktionen kann dann nicht nur auf die Geometriedaten, sondern auch auf die Beziehungen, auf denen die Bauteilstruktur basiert, zugegriffen werden.

This research has developed several models and methodologies with the aim of improving the accuracy and applicability of reliability predictions for complex repairable systems. A repairable system is usually defined as one that will be repaired to recover its functions after each failure. Physical assets such as machines, buildings, vehicles are often repairable. Optimal maintenance strategies require the prediction of the reliability of complex repairable systems accurately. Numerous models and methods have been developed for predicting system reliability. After an extensive literature review, several limitations in the existing research and needs for future research have been identified. These include the follows: the need for an effective method to predict the reliability of an asset with multiple preventive maintenance intervals during its entire life span; the need for considering interactions among failures of components in a system; and the need for an effective method for predicting reliability with sparse or zero failure data. In this research, the Split System Approach (SSA), an Analytical Model for Interactive Failures (AMIF), the Extended SSA (ESSA) and the Proportional Covariate Model (PCM), were developed by the candidate to meet the needs identified previously, in an effective manner. These new methodologies/models are expected to rectify the identified limitations of current models and significantly improve the accuracy of the reliability prediction of existing models for repairable systems. The characteristics of the reliability of a system will alter after regular preventive maintenance. This alternation makes prediction of the reliability of complex repairable systems difficult, especially when the prediction covers a number of imperfect preventive maintenance actions over multiple intervals during the asset's lifetime. The SSA uses a new concept to address this issue effectively and splits a system into repaired and unrepaired parts virtually. SSA has been used to analyse system reliability at the component level and to address different states of a repairable system after single or multiple preventive maintenance activities over multiple intervals. The results obtained from this investigation demonstrate that SSA has an excellent ability to support the making of optimal asset preventive maintenance decisions over its whole life. It is noted that SSA, like most existing models, is based on the assumption that failures are independent of each other. This assumption is often unrealistic in industrial circumstances and may lead to unacceptable prediction errors. To ensure the accuracy of reliability prediction, interactive failures were considered. The concept of interactive failure presented in this thesis is a new variant of the definition of failure. The candidate has made several original contributions such as introducing and defining related concepts and terminologies, developing a model to analyse interactive failures quantitatively and revealing that interactive failure can be either stable or unstable. The research results effectively assist in avoiding unstable interactive relationship in machinery during its design phase. This research on interactive failures pioneers a new area of reliability prediction and enables the estimation of failure probabilities more precisely. ESSA was developed through an integration of SSA and AMIF. ESSA is the first effective method to address the reliability prediction of systems with interactive failures and with multiple preventive maintenance actions over multiple intervals. It enhances the capability of SSA and AMIF. PCM was developed to further enhance the capability of the above methodologies/models. It addresses the issue of reliability prediction using both failure data and condition data. The philosophy and procedure of PCM are different from existing models such as the Proportional Hazard Model (PHM). PCM has been used successfully to investigate the hazard of gearboxes and truck engines. The candidate demonstrated that PCM had several unique features: 1) it automatically tracks the changing characteristics of the hazard of a system using symptom indicators; 2) it estimates the hazard of a system using symptom indicators without historical failure data; 3) it reduces the influence of fluctuations in condition monitoring data on hazard estimation. These newly developed methodologies/models have been verified using simulations, industrial case studies and laboratory experiments. The research outcomes of this research are expected to enrich the body of knowledge in reliability prediction through effectively addressing some limitations of existing models and exploring the area of interactive failures.

Cette thèse présente une contribution sur les problèmes de contrôle de réseaux d'irrigations en tenant compte des contraintes de communication grâce à une approche multicouches d’intelligence distribuée. Les analyses détaillées de chaque couche avec les résultats analytiques et les simulations seront décrites dans les différents chapitres. Ils mettent l'accent sur l'intérêt de l'approche multicouches, plus précisément sur son efficacité et sa fiabilité pour la supervision, l'optimisation multi-objectifs et le contrôle coopératif distribué sur des systèmes complexes de transport d'eau.La première couche analysé est le réseau hydraulique composé de canaux d’écoulements à surface libre, de sous-réseaux maillés de tuyaux sous pression et des structures hydrauliques (pompes vannes, ..). En intégrant les équations de Saint-Venant pour décrire l’écoulement physique des fluides en surface libre et la méthode Lattice Boltzmann pour la simulation du fluide, nous obtenons un modèle non linéaire discret pour les canaux à surface libre. Les structures hydrauliques sont généralement traitées comme des limites internes des biefs (tronçons) et modélisées par des relations entre les variables de flux et de pression.Permettant l'échange d'informations entre les éléments du système de contrôle, le réseau de communication sera considéré comme la deuxième couche. La résolution des problèmes d’hétérogénéités des systèmes et des communications (par exemple les retards de diffusion dans le réseau, la perte de paquets, la consommation d'énergie) sera étudié en introduisant une architecture de réseau hybride avec un routage dynamique basé sur les exigences de Qualité de Service (QoS) des applications de contrôle. Pour le routage dynamique dans le réseau, une composition pondérée de certaines métriques standards est proposée afin que le protocole de routage utilisant cette métrique composite converge sans boucle avec une « route » optimum. Grâce à différents scénarios de simulation, plusieurs critères de performance du réseau ont été évalués. La comparaison des résultats de simulation permet de valider l'intérêt de cette approche de composition pour le routage dynamique.Une troisième couche propose un système de contrôle réactif optimal développé pour la régulation du réseau d'irrigation dans un modèle étendue à grande échelle : Distributed Cooperative Model Predictive Control (DCMPC). Cette partie aborde la mise en œuvre de différentes stratégies de contrôle (centralisées, décentralisées et distribuées) et intègre la communication coopérative entre les contrôleurs MPC locaux afin d’améliorer les performances global es du système. La gestion de la divergence dans l'échange d'informations entre les contrôleurs est considérée comme un problème de consensus et résolue en utilisant un protocole de consensus asynchrone. Cette approche du contrôle distribué basée sur le paradigme des systèmes multi-agents, fournit une solution garantissant que tous les contrôleurs aient une vue cohérente de certaines valeurs des données nécessaires pour le calcul de décision. Un cas d’application sur un canal d'irrigation est étudié dans les simulations. La comparaison des résultats de simulations valide les avantages de l'approche du contrôle distribué coopératif par rapport aux autres stratégies de contrôle. / This thesis presents control problems of irrigation network with communication constraints and a multi-layer approach to solve these problems in a distributed manner. Detailed discussions of each layer with analytical and simulation results are described throughout several chapters. They emphasize the potential interest of the multi-layer approach, more precisely its efficiency and reliability for supervision, multi-objective optimization and distributed cooperative control of complex water transport systems. Conventionally, the first layer to be considered is the hydraulic network composed of free-surface channels, hydraulic structures and mesh subnetwork of pressurized pipes. By coupling the Saint-Venant equations for describing the physics of free-surface fluid and the Lattice Boltzmann method for the fluid simulation, a discrete-time nonlinear model is obtained for channel reaches. The hydraulic structures are usually treated as internal boundaries of reaches and modeled by algebraic relationships between the flow and pressure variables. To enable the exchange of information among the control system’s components, a communication network is considered in the second layer. Solving challenging problems of heterogeneous devices and communication issues (e.g., network delay, packet loss, energy consumption) is investigated in this thesis by introducing a hybrid network architecture and a dynamic routing design based on Quality of Service (QoS) requirements of control applications. For network routing, a weighted composition of some standard metrics is proposed so that the routing protocol using the composite metric achieves convergence, loop-freeness and path-optimality properties. Through extensive simulation scenarios, different network performance criteria are evaluated. The comparison of simulation results can validate the interest of this composition approach for dynamic routing. Finally, the third layer introduces an optimal reactive control system developed for the regulatory control of large-scale irrigation network under a Distributed Cooperative Model Predictive Control (DCMPC) framework. This part discusses the implementation of different control strategies (e.g., centralized, decentralized, and distributed strategies) and how the cooperative communication among local MPC controllers can be included to improve the performance of the overall system. Managing divergent (or outdated) information exchange among controllers is considered in this thesis as a consensus problem and solved by an asynchronous consensus protocol. This approach based on the multi-agent system paradigm to distributed control requires each controller to agree with its neighbors on some data values needed during action computation. For simulations, a particular benchmark of an irrigation channel is considered. The comparison of simulation results validate the benefits of the distributed cooperative control approach over other control strategies.