With the promise to shape the future of industry, multi-agent robotic technologies have the potential to change many aspects of daily life. Over the coming decade, they are expected to impact transportation systems, military applications such as reconnaissance and surveillance, search-and-rescue operations, or space missions, as well as provide support to emergency first responders. Motivated by the latest developments in the field of robotics, this thesis contributes to the evolution of the future generation of multi-agent robotic systems as they become smarter, more accurate, and diversified in terms of applications. But in order to achieve these goals, the individual agents forming cooperative robotic systems need to be specialized in what they can accomplish, while ensuring accuracy and preserving the ability to perform diverse tasks. This thesis addresses the problem of task allocation in swarm robotics in the specific context where specialized capabilities of the individual agents are considered. Based on the assumption that each individual agent possesses specialized functional capabilities and that the expected tasks, which are distributed in the surrounding environment, impose specific requirements, the proposed task allocation mechanisms are formulated in two different spaces. First, a rudimentary form of the team members’ specialization is formulated as a cooperative control problem embedded in the agents’ dynamics control space. Second, an advanced formulation of agents’ specialization is defined to estimate the individual agents’ task allocation probabilities in a dedicated specialization space, which represents the core contribution of this thesis to the advancement and practice in the area of swarm robotics. The original task allocation process formulated in the specialization space evolves through four stages of development. First, a task features recognition stage is conceptually introduced to leverage the output of a sensing layer embedded in robotic agents to drive the proposed task allocation scheme. Second, a matching scheme is developed to best match each agent’s specialized capabilities with the corresponding detected tasks. At this stage, a general binary definition of agents’ specialization serves as the basis for task-agent association. Third, the task-agent matching scheme is expanded to an innovative probabilistic specialty-based task-agent allocation framework to generalize the concept and exploit the potential of agents’ specialization consideration. Fourth, the general framework is further refined with a modulated definition of the agents’ specialization based on their mechanical, physical structure, and embedded resources. The original framework is extended and a prioritization layer is also introduced to improve the system’s response to complex tasks that are characterized based on the recognition of multiple classes. Experimental validation of the proposed specialty-based task allocation approach is conducted in simulation and on real-world experiments, and the results are presented and discussed in light of potential applications to demonstrate the effectiveness and efficiency of the proposed framework.

With the recent development of reliable autonomous technologies for small unmanned air vehicles (UAVs), the algorithms utilizing teams of these vehicles are becoming an increasingly important research area. Unfortunately, there is no unified framework into which all (or even most) cooperative control problems fall. Five factors that affect the development of cooperative control algorithms are objective coupling, communication, completeness, robustness, and efficiency. We classify cooperative control algorithms by these factors and then present three algorithms with application to target and perimeter surveillance and a method for decentralized algorithm design. The primary contributions of this research are the development and analysis of decentralized algorithms for perimeter and target surveillance. We pose the cooperative perimeter surveillance problem and offer a decentralized solution that accounts for perimeter growth (expanding or contracting) and insertion/deletion of team members. By identifying and sharing the critical coordination information and by exploiting the known communication topology, only a small communication range is required for accurate performance. Convergence of the algorithm to the optimal configuration is proven to occur in finite-time. Simulation and hardware results are presented that demonstrate the applicability of the solution. For single target surveillance, a team of UAVs angularly spaced (i.e. in the splay state configuration) provides the best coverage of the target in a wide variety of circumstances. We propose a decentralized algorithm to achieve the splay state configuration for a team of UAVs tracking a moving target and derive the allowable bounds on target velocity to generate a feasible solution as well as show that, near equilibrium, the overall system is exponentially stable. Monte Carlo simulations indicate that the surveillance algorithm is asymptotically stable for arbitrary initial conditions. We conclude with high fidelity simulation and actual flight tests to show the applicability of the splay state controller to unmanned air systems.

Wind energy is on an upswing due to climate concerns and increasing energy demands on conventional sources. Wind energy is attractive and has the potential to dramatically reduce the dependency on non-renewable energy resources. With the increase in wind farms there is a need to improve the efficiency in power allocation and power generation among wind turbines. Wake interferences among wind turbines can lower the overall efficiency considerably, while offshore conditions pose increased loading on wind turbines. In wind farms, wind turbines* wake affects each other depending on their positions and operation modes. Therefore it becomes essential to optimize the wind farm power production as a whole than to just focus on individual wind turbines. The work presented here develops a hierarchical power optimization algorithm for wind farms. The algorithm includes a cooperative level (or higher level) and an individual level (or lower level) for power coordination and planning in a wind farm. The higher level scheme formulates and solves a quadratic constrained programming problem to allocate power to wind turbines in the farm while considering the aerodynamic effect of the wake interaction among the turbines and the power generation capabilities of the wind turbines. In the lower level, optimization algorithm is based on a leader-follower structure driven by the local pursuit strategy. The local pursuit strategy connects the cooperative level power allocation and the individual level power generation in a leader-follower arrangement. The leader, could be a virtual entity and dictates the overall objective, while the followers are real wind turbines considering realistic constraints, such as tower deflection limits. A nonlinear wind turbine dynamics model is adopted for the low level study with loading and other constraints considered in the optimization. The stability of the algorithm in the low level is analyzed for the wind turbine angular velocity. Simulations are used to show the advantages of the method such as the ability to handle non-square input matrix, non-homogenous dynamics, and scalability in computational cost with rise in the number of wind turbines in the wind farm.

L'adoption récente et généralisée des systèmes d'automatisation des véhicules, avec l’incorporation de la connectivité entre voitures, a encouragé l’utilisation des techniques comme le Contrôle Croisière Adaptatif Coopératif (CACC) et la conduite en convoi. Ces techniques ont prouvé l’amélioration du flux de trafic et la sécurité de la conduite, tout en réduisant la consommation d’énergie et les émissions CO_2. Néanmoins, la robustesse et la stabilité stricte du convoi, malgré les délais de communication et l’hétérogénéité des convois, restent des sujets de recherche en cours. Cette thèse a pour sujet la conception, l’analyse et validation de systèmes de contrôle pour le car-following automatisé et coopératif, en ciblant l’augmentation de ses avantages et son usage, en se concentrant sur la robustesse et la stabilité du convoi même sur des séries de véhicules hétérogènes avec des retards de communication. Une structure feedforward/feedback est développée, dont sa modularité est fondamentale pour la mise au point des approches avec des objectifs différents mais complémentaires. L’architecture permet non seulement l’adoption d’une stratégie d’espacement pour la range entière de vitesse, mais elle peut aussi être employée dans le cadre d’un CACC basé sur une machine d’état pour la conduite en convoi sur des environnements urbains avec des capacités de freinage d’urgence et de rejoint du convoi. Des différents algorithmes pour la conception de systèmes de contrôle feedback pour la régulation des distances sont présentés, pour quoi le calcul d’ordre fractionnaire démontre fournir des réponses fréquentielles de boucle fermé plus précises et satisfaire des besoins plus exigeantes. La performance est assurée malgré l’hétérogénéité avec la proposition de deux approches feedforward différents. Le premier est basé sur une topologie en considérant que le véhicule précédent dans la boucle, tandis que le deuxième inclut le véhicule leader pour améliorer la performance de suivi. Les algorithmes proposés sont validés avec des études de stabilité dans le domaine du temps et fréquence, ainsi que simulations et expérimentations réelles. / Recent widespread adoption of vehicle automation and introduction of vehicle-to-vehicle connectivity has opened the doors for techniques as Cooperative Adaptive Cruise Control (CACC) and platooning, showing promising results in terms of traffic capacity and safety improvement, while reducing fuel consumption and CO_2 emissions. However, robustness and strict string stability, despite communication delays and string heterogeneity is still an on-going research field. This thesis deals with the design, study and validation of control systems for cooperative automated car-following, with the purpose of extending their benefits and encourage their employment, focusing on robustness and string stability, despite possible V2V communication delays and string heterogeneity. A feedforward/feedback hierarchical control structure is developed, which modularity is fundamental for the proposal of approaches that target different but complementary performance objectives. The architecture not only permits the adoption of a full speed range spacing policy that target multiple criteria, but can also be employed in a state machine-based CACC framework for urban environments with emergency braking and platoon re-joining capabilities in case of pedestrian interaction. Different feedback control design algorithms are presented for the gap-regulation, for which the fractional-order calculus is demonstrated to provide more accurate closed loop frequency responses and satisfy more demanding requirements. Desired performance is ensured in spite of string heterogeneity through the proposal of two feedforward methods : one based on predecessor-only topology, while the second includes the leader vehicle information on feedforward to gain tracking capabilities. Proposed control algorithms are validated through time and frequency-domain stability studies, simulation and real platforms experiments.

Hoje em dia com o crescente aumento da exploração de petróleo e gás em águas profundas, há um aumento na demanda por operações offshore envolvendo a cooperação entre unidades flutuantes. Tais operações requerem um alto nível de planejamento e coordenação, o que na maioria dos casos é feito com a troca de informação no nível de operação, com cada unidade flutuante comandada independentemente. Exemplos de operações deste tipo vão desde operações de alívio passando por operações de instalação de equipamento submarino, até operações de pesquisa envolvendo múltiplas unidades flutuantes dotadas de sistema de posicionamento dinâmico (DP). As vantagens do controle cooperativo surgem com a redução do erro da distância relativa durante a manutenção do posicionamento ou durante a execução de manobras de posicionamento conjuntas. No presente trabalho, os conceitos de controle de consenso são aplicados de forma combinada com o sistema DP de cada navio. A influência dos ganhos do controlador cooperativo no sistema como um todo será discutida, utilizando-se técnicas de análise da resposta em frequência. Simulações completas no domínio do tempo e experimentos usando modelos em escala serão utilizados para se demonstrar o funcionamento do controle cooperativo. Todas as simulações serão conduzidas no simulador Dynasim e os ensaios experimentais no tanque de provas da Engenharia Naval da Escola Politécnica da Universidade de São Paulo. Além disso, serão feitas comparações entre os experimentos em tanque de provas e simulações numéricas equivalentes, demonstrando-se a validade dos ensaios numéricos. Será também demonstrado que os requisitos de projetos adotados são atendidos pelos ensaios em tanque de provas. . / With the increasing of deep water oil & gas exploration, there is also an increase in the demand by offshore operations involving muti-vessels. Such operations require a high level of planning and coordination, which in most of the cases is made by information exchange at the operation level, being each vessel commanded independently. Examples of such operations are offloading, subsea equipment installation and subsea research operation; all of them involving multiples dynamically positioned (DP) vessels. The advantage of the cooperative control arises with the reduction of the relative positioning error during station keeping or transient maneuvers. In this work, the consensus control concepts are applied combined with the DP System of each ship. The cooperative DP controller will be investigated with the analysis of the coupled dynamics of the vessels. The influence of the cooperative control gains on the whole system will be discussed, using the frequency response of the open loop system. Fully nonlinear time-domain simulations and experimental results will be used to demonstrate the operation of the cooperative control. Besides that, comparisons between the small-scale experiments and equivalent numerical simulations will be carried out, validating the experimental results. It will also be demonstrated that the adopted design requirements are met. All tests will be carried out using the Dynasim numerical simulator and the small-scale experiments will be carried on the academic towing tank in the Naval Architecture and Ocean Engineering Department, Polytechnic School of University de São Paulo.

Le travail présenté dans ce mémoire de thèse porte sur la tolérance aux défauts dans le cas des systèmes linéaires. Les moyens de communication numériques sont utilisés dans le cadre de la mise en oeuvre d'une architecture de commande tolérante aux défauts pour des systèmes complexes. Une coopération entre les modules de commande/diagnostic assure la tolérance à certains types de défauts qui affectent le système. La commande des systèmes est traditionnellement réalisée à partir d'un calculateur central qui collecte l'ensemble des informations relevées sur le procédé, puis les traite pour élaborer un ensemble de commande qui est appliqué au procédé. Avec le développement des systèmes commandés en réseaux (Networked Control System) et des systèmes embarqués, l'architecture des systèmes s'oriente vers une distribution des algorithmes de commande et de diagnostic. On se propose d'aborder le problème de la conception des stratégies de distribution de diagnostic/commande et de coopération des tâches de commande entre les sous-contrôleurs associés à chaque sous-système qui composent le système complexe et de prendre en compte les défauts des actionneurs et de capteurs affectant les sous-systèmes. Il s'agit alors d'élaborer une stratégie de commande coopérative visant à compenser les effets des défauts affectant le système. Les commandes locales sont des commandes prédictives à base de modèle (MPC: Model Predictive Control). Une analyse de stabilité a été faite en prenant en considération la défaillance du réseau de communication. / The work presented in this memory of thesis focuses on fault tolerance in the case of linear systems. Digital communication tools are used in the context of the implementation of an architecture for fault tolerant control of complex systems. A cooperation between the control/diagnosis blocks ensures the tolerance to certain types of faults which affect the system. Control systems is traditionally carried out starting from a central computer that collects all information gathered on the process. Then, these information are treated in order to develop a set of command which is applied to the process. Thanks to the development of the Networked System Control and embedded systems, systems architecture is oriented towards a distributed control and diagnostic algorithms. One proposes to address the problem of designing distribution strategies for diagnosis/control and control tasks cooperation between sub-controllers associated at each subsystem comprising the complex system and to take into account the faults on the actuators and sensors that affect the subsystems. Then a cooperative control strategy is proposed. It aims at compensating the effects of the faults affecting the system. Local controls are based on Model Predictive Control (MPC). An analysis of stability was made taking into account the failure of the communication network

Cette thèse considère principalement trois problèmes dans le domaine du contrôle distribué coopératif des systèmes multi-agents(SMA): le consensus, la navigation en formation et le maintien en formation d’un groupe d’agents lorsqu’un agent disparait. Nous proposons 3 algorithmes pour résoudre le problème du calcul distribué d’un consensus à partir de l’approche leadeur-suiveur dans le contexte SMA à dynamique non-linéaire. La référence est définie comme un leader virtuel dont on n’obtient, localement, que les données de position et de vitesse. Pour résoudre le problème du suivi par consensus pour les SMA à dynamique non-linéaire, nous considérons le suivi par consensus pour SMA de premier ordre. On propose des résultats permettant aux suiveurs de suivre le leadeur virtuel en temps fini en ne considérant que les positions des agents. Ensuite, nous considérons le suivi par consensus de SMA de second. Dans le cas de la planification de trajectoire et la commande du mouvement de la formation multi-agents. L’idée est d’amener la formation, dont la dynamique est supposée être en 3D, d’une configuration initiale vers une configuration finale (trouver un chemin faisable en position et orientation) en maintenant sa forme tout le long du chemin en évitant les obstacles. La stratégie proposée se décompose en 3 étapes. Le problème du Closing-Rank se traduit par la réparation d’une formation rigide multi-agents "endommagée" par la perte de l'un de ses agents. Nous proposons 2 algorithmes d’autoréparation systématique pour récupérer la rigidité en cas de perte d'un agent. Ces réparations s’effectuent de manière décentralisée et distribuée n’utilisant que des informations de voisinage / This dissertation focuses on distributed cooperative control of multi-agent systems. First, the leader-following consensus for multi-agent systems with nonlinear dynamics is investigated. Three consensus algorithms are proposed and some sufficient conditions are obtained for the states of followers converging to the state of virtual leader globally exponentially. Second, the consensus tracking for multi-agent systems with nonlinear dynamics is investigated. Some consensus tracking algorithms are developed, and some sufficient conditions are obtained. Based on these consensus tracking algorithms and sufficient conditions, it is shown that in first-order multi-agent systems all followers can track the virtual leader in finite time, and in second-order multi-agent systems the consensus tracking can be achieved at least globally exponentially. Third, the path planning and motion control of multi-agent formation is studied, where a practical framework is provided. In order to find a collision-free and deadlock-free feasible path for the whole formation, an optimizing algorithm is given to optimize the path generated by A* search algorithm. In order to realize the cohesive motion of a persistent formation in 3-dimensional space, a set of decentralized control laws is designed. Finally, the formation keeping problem is studied. We mainly focus on the closing ranks problem, which deals with the addition of links to a rigid multi-agent formation that is “damaged" by losing one of its agents, in order to recover rigidity. Some graph theoretical results are obtained, and some systematic ’self-repair’ operations are proposed to recover the rigidity in case of agent removals

Automation has become increasingly prevalent in all forms of society. Activities that are too difficult for a human or to dangerous can be done by machines which do not share those downsides. In addition, tasks can be scheduled more precisely and accurately. Increases in the autonomy have allowed for a new level of tasks which are completed by teams of automated agents rather than a single one, called cooperative control. This has many benefits; but comes at the cost of increased complexity and coordination. The main thrust of research in this field is problem based, considering communication issues as a secondary feature. There is a gap considering problems in which many changes occur as rapidly as communication and the issues that arise as a result. This is the main motivation. This research presents an approach to cooperative control in highly variable systems and tackles some of the issues present in such a system. One of the most important issues is the communication network itself, which is used as an indicator for how healthy the system is an how well it may react to future changes. Therefore using the network as an input to control allows the system to navigate between conservative and aggressive techniques to improve performance while still maintaining robustness. Results are based on a test bed designed to simulate a wide variety of problem types based on: network type; numbers of actors; frequency of changes; impact of changes and method of change. The developed control method is compared to the baseline case ignoring cooperation as well as an idealized case assuming perfect system knowledge. The baseline represents sacrifices coordination to achieve a high level of robustness at reduced performance while the idealized case represents the best possible performance. The control techniques developed give a performance at least as good as the baseline case if not better for all simulations.

Cooperative control enables combinations of sensor data from multiple autonomous underwater vehicles (AUVs) so that multiple AUVs can perform smarter behaviors than a single AUV. In addition, in some situations, a human-driven underwater vehicle (HUV) and a group of AUVs need to collaborate and preform formation behaviors. However, the collective dynamics of a fleet of heterogeneous underwater vehicles are more complex than the non-trivial single vehicle dynamics, resulting in challenges in analyzing the formation behaviors of a fleet of heterogeneous underwater vehicles. The research addressed in this dissertation investigates the collective dynamics and control of a fleet of heterogeneous underwater vehicles, including multi-AUV systems and systems comprised of an HUV and a group of AUVs (human-AUV systems). This investigation requires a mathematical motion model of an underwater vehicle. This dissertation presents a review of a six-degree-of-freedom (6DOF) motion model of a single AUV and proposes a method of identifying all parameters in the model based on computational fluid dynamics (CFD) calculations. Using the method, we build a 6DOF model of the EcoMapper and validate the model by field experiments. Based upon a generic 6DOF AUV model, we study the collective dynamics of a multi-AUV system and develop a method of decomposing the collective dynamics. After the collective dynamics decomposition, we propose a method of achieving orientation control for each AUV and formation control for the multi-AUV system. We extend the results and propose a cooperative control for a human-AUV system so that an HUV and a group of AUVs will form a desired formation while moving along a desired trajectory as a team. For the post-mission stage, we present a method of analyzing AUV survey data and apply this method to AUV measurement data collected from our field experiments carried out in Grand Isle, Louisiana in 2011, where AUVs were used to survey a lagoon, acquire bathymetric data, and measure the concentration of reminiscent crude oil in the water of the lagoon after the BP Deepwater Horizon oil spill in the Gulf of Mexico in 2010.

Une structure de contrôle distribué partiellement coopérative est proposée dans cette thèse. La structure est consacrée au problème de commande d’un réseau composé de sous-systèmes non linéaires/linéaires qui sont interconnectés par leurs états et les entrées de commande. Par la coopération partielle, cela signifie que chaque sous-système est capable de préserver son propre objectif en utilisant un indice de la coopération ajustable qui définit dans quelle mesure il accepte de dégrader son propre niveau de performance afin d’aider ses voisins à maintenir leur intégrité sous les interconnexions potentiellement déstabilisantes. La communication entre les sous-systèmes est basée sur l’échange de niveaux de fonction de Lyapunov avec les contraintes associées et la quantité d’information transmise est plutôt réduite par rapport aux travaux les plus récents. Une autre caractéristique intéressante de cet structure de contrôle distribué non linéaire coopératif est l’utilisation de vecteurs prioritaires par chaque sous-système. Ce vecteur définit un ordre hiérarchique de l’importance de ses voisins menant à une stratégie de coopération dans lequel les sous-systèmes critiques dans le réseau peuvent être préservés en dépit des interactions. Une version linéaire de la structure de contrôle distribué coopératif est présenté. Cette conception de structure linéaire conduit à une évaluation rigoureuse de stabilité du réseau en boucle fermée globale. Une méthode d’amélioration de la stabilité est proposée basée sur la résolution d’un problème d’optimisation non convexe avec des degrés de liberté liés au paramétrage de l’affectation de priorité. Pour montrer son efficacité, le contrôle distribué coopératif proposé pour le réseau linéaire est appliqué pour traiter le problème de contrôle de la fréquence de charge dans un réseau d’alimentation et le problème de contrôle du système cryogénique. / In this dissertation, a partially cooperative distributed control framework is proposed. The framework is dedicated to the control problem for a network consisting of linear/nonlinear subsystems that are interconnected through their states and control inputs. By partial cooperation, it means that each subsystem is able to preserve its own objective while using a tunable cooperation index that defines to what extend it accepts to degrade its own performance level so as to help its neighbors maintain their integrity under potentially destabilizing interconnections. The communication between the subsystems is rather reduced comparing to most of the existing contributions. Another attractive feature of the proposed framework is that each subsystem in the network can be assigned with priority indicating the importance of the corresponding subsystem seen by its neighbors. Through proper parameterization of the priority assignment, improved performance of the subsystems and the network can be acheived. In the linear version, a rigorous stability assessment method is presented and a systematic way of proposing an optimized priority assignment for a given network is introduced as well. The proposed scheme is applied to handle the load frequency control problem in a 4-area power network and the control problem of a cryogenic system to illustrate its effectiveness.