Multi-vehicle systems offer many advantages in engineering applications such as increased efficiency and robustness. However, the disadvantage of multi-vehicle systems is that they require a high level of organization and coordination in order to successfully complete a task. Formation control is a field of engineering that addresses this issue, and provides coordination schemes to successfully implement multi-vehicle systems. Two approaches to group coordination were proposed in this work: geometric and self-organizing formations. A geometric reconfiguring formation was developed using the leader-follower method, and the self-organizing formation was developed using the velocity potential equations from fluid flow theory. Both formation controllers were first tested in simulation in MATLAB, and then implemented on the X80 mobile robot units. Various experiments were conducted to test the formations under difficult obstacle scenarios. The robots successfully navigated through the obstacles as a coordinated as a team using the self-organizing and geometric formation control approaches.

Multi-vehicle systems offer many advantages in engineering applications such as increased efficiency and robustness. However, the disadvantage of multi-vehicle systems is that they require a high level of organization and coordination in order to successfully complete a task. Formation control is a field of engineering that addresses this issue, and provides coordination schemes to successfully implement multi-vehicle systems. Two approaches to group coordination were proposed in this work: geometric and self-organizing formations. A geometric reconfiguring formation was developed using the leader-follower method, and the self-organizing formation was developed using the velocity potential equations from fluid flow theory. Both formation controllers were first tested in simulation in MATLAB, and then implemented on the X80 mobile robot units. Various experiments were conducted to test the formations under difficult obstacle scenarios. The robots successfully navigated through the obstacles as a coordinated as a team using the self-organizing and geometric formation control approaches.

L’objectif de cette thèse est de développer et étudier des modèles mathématiques d’échanges économiques, basés sur la flexibilité de la demande, entre fournisseurs et consommateurs d’électricité. D’une part, des fournisseurs d’électricité offrent des prix dépendant de l’heure de consommation. D’autre part, des consommateurs adaptent leur usage, minimisant leur facture et le désagrément lié aux changements de consommation induits. La structure de ces problèmes correspond à des problèmes d’optimisation bi-niveau. Trois types de modèles sont étudiés. Tout d’abord, l’interaction entre un fournisseur et un opérateur de smart grid est modélisée par un problème à un seul meneur et un seul suiveur. Pour cette première approche, le niveau de détails du suiveur est particulièrement élevé, et inclut notamment une gestion stochastique de la production distribuée. La meilleure réponse d’un fournisseur dans un modèle à plusieurs meneurs et plusieurs suiveurs fait l’objet de la seconde partie de la thèse. Celle-ci intègre aussi la possibilité d’avoir des agrégateurs comme suiveurs. Deux nouvelles méthodes de résolution reposant sur la sélection d’équilibres de Nash entre suiveurs sont proposées. Enfin, dans une troisième et dernière partie, on se focalise sur la recherche d’équilibres non coopératifs pour ce modèle à plusieurs meneurs et plusieurs suiveurs.Tous les problèmes abordés dans cette thèse le sont non seulement d’un point de vue théorique, mais également d’un point de vue numérique / The objective of this thesis is to develop and study mathematical models of economical exchanges between energy suppliers and consumers, using demand-side management. On one hand, the suppliers offer time-of-use electricity prices. On the other hand, energy consumers decide on their energy demand schedule, minimizing their electricity bill and the inconvenience due to schedule changes. This problem structure gives rise to bilevel optimization problems.Three kinds of models are studied. First, single-leader single-follower problems modeling the interaction between an energy supplier and a smart grid operator. In this first approach, the level of details is very high on the follower’s side, and notably includes a stochastic treatment of distributed generation. Second, a multi-leader multi-follower problem is studied from the point of view of the best response of one of the suppliers. Aggregators are included in the lower level. Two new resolution methods based on a selection of Nash equilibriums at the lower level are proposed. In the third and final part, the focus is on the evaluation of noncooperative equilibriums for this multi-leader multi-follower problem.All the problems have been studied both from a theoretical and numerical point of view.

Retention of qualified and experienced employees is the greatest challenge faced by nonprofit organizations. Using transformational leadership theory, the purpose of this single-case study was to explore strategies used by managers of nonprofit organizations to increase employee retention. The population for this study included 3 managers of one nonprofit organization in Texarkana, Texas, with tenure of at least 2 years. These managers had successfully implemented retention strategies to retain qualified and experienced employees for more than 2 years. Collected data included semistructured, face-to-face interviews and from archived documents that pertained to employee retention in nonprofit organizations. The data analysis process comprised 5 steps: compiling, disassembling data for coding, reassembling, interpreting, and reporting data themes. The use of member checking and methodological triangulation increased the trustworthiness of interpretations. The 2 themes that emerged from this study were motivational incentives and effective communication. The implications for positive social change in the nonprofit sector include sustaining the workforce by retaining qualified and experienced employees. With less employee turnover, nonprofit leaders may experience real cost savings. Nonprofit leaders may find the cost savings beneficial in extending available funds for services to local communities.

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The use of unmanned aerial vehicles (UAV), so-called drones, has been growingrapidly in the last decade. Today, they are used for, among other things, monitoring missions and inspections of places that are difficult for people to access. Toefficiently and robustly execute these types of missions, a swarm of drones maybe used, i.e., a collection of drones that coordinate together. However, this introduces new requirements on what solutions are used for control and navigation. Two important aspects of autonomous navigation of drone swarms are formationcontrol and collision avoidance. To manage these problems, we propose four different solution algorithms. Two of them use leader-follower control to keep formation, Artificial PotentialField (APF) for path planning and Control Barrier Function (CBF)/ExponentialControl Barrier Function (ECBF) to guarantee that the control signal is safe i.e.the drones keep the desired safety distance. The other two solutions use an optimal control problem formulation of a motion planning problem to either generate open-loop or closed-loop trajectories with a linear quadratic regulator (LQR)controller for trajectory following. The trajectories are optimized in terms of timeand formation keeping. Two different controllers are used in the solutions. Oneof which uses cascade PID control, and the other uses a combination of cascadePID control and LQR control. As a way to test our solutions, a scenario is created that can show the utilityof the presented algorithms. The scenario consists of two drone swarms that willtake on different missions executed in the same environment, where the droneswarms will be on a direct collision course with each other. The implementedsolutions should keep the desired formation while smoothly avoiding collisionsand deadlocks. The tests are conducted on real UAVs, using the open sourceflying development platform Crazyflie 2.1 from Bitcraze AB. The resulting trajectories are evaluated in terms of time, path length, formation error, smoothnessand safety.  The obtained results show that generating trajectories from an optimal control problem is superior compared to using APF+leader-follower+CBF/ECBF. However, one major advantage of the last-mentioned algorithms is that decision making is done at every time step making these solutions more robust to disturbancesand changes in the environment.

Introduction: The co-construction of leadership is a relatively new theoretical concept thatis growing in demand in the field of science. Since our global workforce becomes moreheterogenous and attitudes towards leader-follower relationships evolve, a successfulinteraction between leaders and followers becomes more central to the overall functioningof an organisation. With a global business climate that gradually shifts its focus onemploying more horizontal modes of organising, more emphasis is put on improving thequality of dyadic work relationships. Purpose: The purpose of this study is to explore the esteemed role of follower behaviourin the co-construction of leadership in an intercultural context. Since most literatureemphasis on leader-follower relationships we are interested in exploring a follower-centricperspective on the co-construction of leadership. By adding the aspect of interculturalcontexts, a broader understanding of the impact of culture and communication can beapplied to this study. Research methodology: This study is a case study based on a qualitative research methodwith an inductive research approach. We have held nine recorded semi-structuredinterviews nearly equally spread between leaders and followers with different culturalbackgrounds working for a MNC in the finance industry. We have created a conceptualtheoretical model which was constructed based on findings of empirical data, which isbased on the following five themes - follower behaviour, leader behaviour, working in anintercultural context, leader-follower relationship, and co-construction of leadership. Results and analysis: The result of this study reveals that follower behaviour, leaderbehaviour, dyadic leader-follower relationships, and constructive communication areimportant aspects to have knowledge of to comprehend what actions can be undertaken tofacilitate the co-construction of leadership in an intercultural context. Conclusion: The role of follower behaviour in the co-construction of leadership in anintercultural context plays an active role in the co-constructing of leadership. Bydisplaying certain desirable behaviour and traits, as well as communicating constructively,followers can positively influence leadership. This can be facilitated by leaders that enablefollowers with trust, partnership and growth. In addition, interculturality adds anadditional layer that encompasses diverse perspectives and approaches and encouragespersonal growth.

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Ce travail s’inscrit dans le cadre de la commande d’un système multi agents/ multi véhicules. Cette thèse traite en particulier le cas de la commande d’un système multi-robots mobiles non-holonomes. L'objectif est de concevoir des lois de commandes appropriées pour chaque robot de sorte que l’ensemble des robots puisse exécuter des tâches spécifiques, de suivre des trajectoires désirées tout en maintenant des configurations géométriques souhaitées. L’approche leadeur-suiveur pour la commande d’un groupe de robots mobiles non-holonomes est étudiée en intégrant la technologie backstepping, avec une approche basée sur les neurodynamiques bioinspirées. Le problème de commande distribuée d’un système multi robots sur le consensus est également étudié. Des lois de commandes cinématiques distribuées sont développés afin de garantir au système multi-robots la convergence exponentielle vers une configuration géométrique souhaitée. Afin de tenir compte de la dynamique des paramètres inconnus, des commandes adaptatives de couple sont développés pour que le système multi-robots puisse converger asymptotiquement vers le modèle géométrique souhaité. Lorsque la dynamique est inconnue, des commandes à base de réseaux de neurones sont proposées / This work is based on the multi-agent system / multi-vehicles. This thesis especially focuses on formation control of multiple nonholonomic mobile robots. The objective is to design suitable controllers for each robot according to different control tasks and different constraint conditions, such that a group of mobile robots can form and maintain a desired geomantic pattern and follow a desired trajectory. The leader-follower formation control for multiple nonholonomic mobile robots is investigated under the backstepping technology, and we incorporate a bioinspired neurodynamics scheme in the robot controllers, which can solve the impractical velocity jumps problem. The distributed formation control problem using consensus-based approach is also investigated. Distributed kinematic controllers are developed, which guarantee that the multi-robots can at least exponentially converge to the desired geometric pattern under the assumption of "perfect velocity tracking". However, in practice, "perfect velocity tracking" doesn’t hold and the dynamics of robots should not be ignored. Next, in consideration of the dynamics of robot with unknown parameters, adaptive torque controllers are developed such that the multi-robots can asymptotically converge to the desired geometric pattern under the proposed distributed kinematic controllers. Furthermore, When the partial knowledge of dynamics is available, an asymptotically stable torque controller has been proposed by using robust adaptive control techniques. When the dynamics of robot is unknown, the neural network controllers with the robust adaptive term are proposed to guarantee robust velocity tracking

Un groupe de robots collaboratifs peut gérer des tâches qui sont difficiles, voire impossibles, à accomplir par un seul. On appelle un ensemble de robots coopérant un système multi-agents (SMA). L'interaction entre agents est un facteur clé dans la commande coopérative qui pose d'importants défis théoriques et pratiques. L'une des tâches du contrôle coopératif est le consensus dont l'objectif est de concevoir des protocoles de commande afin de parvenir à un accord entre leurs états respectifs. Cette thèse améliore la navigation pour les SMA, tout en tenant compte de certaines contraintes pratiques (modèle du robot et contraintes temporelles) dans la conception de contrôleurs coopératifs pour chaque agent, de manière décentralisée. Dans cette thèse, deux directions sont étudiées. D'une part, le taux de convergence est une spécification de performance importante pour la conception du contrôleur pour un système dynamique. La convergence rapide est toujours recherchée pour améliorer les performances et la robustesse. La plupart des algorithmes de consensus existants se concentrent sur la convergence asymptotique, où le temps d'établissement est infini. Cependant, de nombreuses applications nécessitent une convergence rapide généralement caractérisée par une stratégie de commande à temps fini. De plus, la commande à temps fini autorise certaines propriétés intéressantes, mais le temps de stabilisation dépend des conditions initiales des agents. L'objectif ici est de concevoir un protocole de consensus leader-follower à temps fixe pour les SMA décrits en temps continu. Ce problème est étudié en utilisant la théorie de la stabilisation à temps fixe, qui garantit que le temps de stabilisation est borné quelles que soient les conditions initiales. Les contrôleurs et les observateurs à modes glissants sont conçus pour que chaque agent résolve le problème du consensus à temps fixe lorsque le leader est dynamique. D'autre part, par rapport aux systèmes à temps continu, le problème du consensus dans un cadre à temps discret convient mieux aux applications pratiques en raison de la limitation des ressources de calcul pour chaque agent. Le modèle de commande prédictive (MPC) permet de gérer les contraintes de commande et d'état des systèmes. Dans cette thèse, cette méthode est appliquée pour traiter le problème du consensus en temps discret en laissant chaque agent résoudre, à chaque étape, un problème de commande optimale contraint impliquant uniquement l'état des agents voisins. Les performances de suivi sont également améliorées dans cette thèse en ajoutant de nouveaux termes à partir du MPC classique. Les contrôleurs proposés sont simulés et implémentés sur un groupe composé de plusieurs robots réels en utilisant ROS (Robotic Operating System). Dans cette thèse, quelques solutions correspondant au problème de la connexion entre plusieurs robots mobiles de manière décentralisée, du réglage des périodes d'échantillonnage et des paramètres de contrôle sont également abordées. / Nowadays, robots have become increasingly important to investigate hazardous and dangerous environments. A group of collaborating robots can often deal with tasks that are difficult, or even impossible, to be accomplished by a single robot. Multiple robots working in a cooperative manner is called as a Multi-Agent System (MAS). The interaction between agents to achieve a global task is a key in cooperative control. Cooperative control of MASs poses significant theoretical and practical challenges. One of the fundamental topics in cooperative control is the consensus where the objective is to design control protocols between agents to achieve a state agreement. This thesis improves the navigation scheme for MASs, while taking into account some practical constraints (robot model and temporal constraints) in the design of cooperative controllers for each agent, in a fully decentralized way. In this thesis, two directions are investigated. On one hand, the convergence rate is an important performance specification to design the controller for a dynamical system. As an important performance measure for the coordination control of MASs, fast convergence is always pursued to achieve better performance and robustness. Most of the existing consensus algorithms focus on asymptotic convergence, where the settling time is infinite. However, many applications require a high speed convergence generally characterized by a finite-time control strategy. Moreover, finite-time control allows some advantageous properties but the settling time depend on the initial states of agents. The objective here is to design a fixed-time leader-follower consensus protocol for MASs described in continuous-time. This problem is studied using the powerful theory of fixed-time stabilization, which guarantee that the settling time is upper bounded regardless to the initial conditions. Sliding mode controllers and sliding mode observers are designed for each agent to solve the fixed-time consensus tracking problem when the leader is dynamic. On the other hand, compared with continuous-time systems, consensus problem in a discrete-time framework is more suitable for practical applications due to the limitation of computational resources for each agent. Model Predictive Control (MPC) has the ability to handle control and state constraints for discrete-time systems. In this thesis, this method is applied to deal with the consensus problem in discrete-time by letting each agent to solve, at each step, a constrained optimal control problem involving only the state of neighboring agents. The tracking performances are also improved in this thesis by adding new terms in the classical MPC technique. The proposed controllers will be simulated and implemented on a team of multiple Mini-Lab Enova Robots using ROS (Robotic Operating System) which is an operating system for mobile robots. ROS provides not only standard operating system services but also high-level functionalities. In this thesis, some solutions corresponding to problem of connection between multiple mobile robots in a decentralized way for a wireless robotic network, of tuning of the sampling periods and control parameters are also discussed.