COOPERATIVE AND CONSENSUS-BASED CONTROL FOR A TEAM OF MULTI-AGENT SYSTEMS

Cooperative control has attracted a noticeable interest in control systems community due to its numerous applications in areas such as formation flying of unmanned aerial vehicles, cooperative attitude control of spacecraft, rendezvous of mobile robots, unmanned underwater vehicles, traffic control, data network congestion control and routing. Generally, in any cooperative control of multi-agent systems one can find a set of locally sensed information, a communication network with limited bandwidth, a decision making algorithm, and a distributed computational capability. The ultimate goal of cooperative systems is to achieve consensus or synchronization throughout the team members while meeting all communication and computational constraints. The consensus problem involves convergence of outputs or states of all agents to a common value and it is more challenging when the agents are subjected to disturbances, measurement noise, model uncertainties or they are faulty. This dissertation deals with the above mentioned challenges and has developed methods to design distributed cooperative control and fault recovery strategies in multi-agent systems. Towards this end, we first proposed a transformation for Linear Time Invariant (LTI) multi-agent systems that facilitates a systematic control design procedure and make it possible to use powerful Lyapunov stability analysis tool to guarantee its consensus achievement. Moreover, Lyapunov stability analysis techniques for switched systems are investigated and a novel method is introduced which is well suited for designing consensus algorithms for switching topology multi-agent systems. This method also makes it possible to deal with disturbances with limited root mean square (RMS) intensities. In order to decrease controller design complexity, a iii method is presented which uses algebraic connectivity of the communication network to decouple augmented dynamics of the team into lower dimensional parts, which allows one to design the consensus algorithm based on the solution to an algebraic Riccati equation with the same order as that of agent. Although our proposed decoupling method is a powerful approach to reduce the complexity of the controller design, it is possible to apply classical pole placement methods to the transformed dynamics of the team to develop and obtain controller gains. The effects of actuator faults in consensus achievement of multi-agent systems is investigated. We proposed a framework to quantitatively study actuator loss-of-effectiveness effects in multi-agent systems. A fault index is defined based on information on fault severities of agents and communication network topology, and sufficient conditions for consensus achievement of the team are derived. It is shown that the stability of the cooperative controller is linked to the fault index. An optimization problem is formulated to minimize the team fault index that leads to improvements in the performance of the team. A numerical optimization algorithm is used to obtain the solutions to the optimal problem and based on the solutions a fault recovery strategy is proposed for both actuator saturation and loss-of-effectiveness fault types. Finally, to make our proposed methodology more suitable for real life scenarios, the consensus achievement of a multi-agent team in presence of measurement noise and model uncertainties is investigated. Towards this end, first a team of LTI agents with measurement noise is considered and an observer based consensus algorithm is proposed and shown that the team can achieve H∞ output consensus in presence of both bounded RMS disturbance input and measurement noise. In the next step a multi-agent team with both linear and Lipschitz nonlinearity uncertainties is studied and a cooperative control algorithm is developed. An observer based approach is also developed to tackle consensus achievement problem in presence of both measurement noise and model uncertainties

Synchronous MDADT-Based Fuzzy Adaptive Tracking Control for Switched Multiagent Systems via Modified Self-Triggered Mechanism

In this paper, a self-triggered fuzzy adaptive switched control strategy is proposed to address the synchronous tracking issue in switched stochastic multiagent systems (MASs) based on mode-dependent average dwell-time (MDADT) method. Firstly, a synchronous slow switching mechanism is considered in switched stochastic MASs and realized through a class of designed switching signals under MDADT property. By utilizing the information of both specific agents under switching dynamics and observers with switching features, the synchronous switching signals are designed, which reduces the design complexity. Then, a switched state observer via a switching-related output mask is proposed. The information of agents and their preserved neighbors is utilized to construct the observer and the observation performance of states is improved. Moreover, a modified self- triggered mechanism is designed to improve control performance via proposing auxiliary function. Finally, by analysing the re- lationship between the synchronous switching problem and the different switching features of the followers, the synchronous slow switching mechanism based on MDADT is obtained. Meanwhile, the designed self-triggered controller can guarantee that all signals of the closed-loop system are ultimately bounded under the switching signals. The effectiveness of the designed control method can be verified by some simulation results

Autonomous Navigation of Quadrotor Swarms

RÉSUMÉ La mise sur le marché de composants toujours plus performants et compétitifs en termes de coût, ainsi que le développement rapide des technologies de commande et de navigation en robotique, nous ont amenés à envisager le contrôle d’un large essaim de quadrirotors. Di-verses solutions impliquant des drones existent déjà pour différentes applications: inventaire forestier, gestion du littoral, suivi du trafic, etc. Parmi celles-ci, la recherche et le sauvetage en situation d’urgence représentent à nos yeux la possibilité la plus intéressante et constitue, de fait, la première motivation de notre travail. Par conséquent, une large revue de littérature sur la question est fournie. Ce travail se concentre sur le contrôle de l’essaim lui-même, et non sur l’application finale. Tout d’abord, un modèle mathématique de la dynamique du quadrirotor est présenté et plusieurs lois de commande numérique sont synthétisées. Ces dernières implémentent les modes de fonctionnement nécessaires aux algorithmes de navigation, à savoir : commande en vitesse, commande en position et commande en suivi. Ensuite, deux solutions originales et complémentaires de contrôle d’essaim sont proposées. D’une part, un algorithme d’essaimage pour la navigation extérieure est développé. Contrairement à la plupart des travaux trouvés dans la littérature, la solution proposée ici gère non seulement le maintien, mais aussi l’initialisation de la formation. Plus spécifiquement, un modèle de formation hexagonale est introduit. Ensuite, les places en formation sont attribuées de façon optimale à l’aide de l’algorithme hongrois. Enfin, les agents se déplacent jusqu’à la place qui leur est assignée tout en évitant les autres agents avec un algorithme de navigation inspiré du Artificial Potential Field. De plus, cette solution tient compte de contraintes de conception réalistes et a été intégrée avec succès dans un logiciel embarqué de quadrotor déjà existant et opérationnel. Les résultats de simulations Software-In-The-Loop sont fournis. D’autre part, une solution d’essaimage pour la navigation intérieure est étudiée. L’algorithme proposé implémente un certain nombre de comportements individuels simples, de sorte qu’un grand essaim peut suivre un meneur dans des environnements encombrés en se fiant uniquement aux informations locales. Des simulations préliminaires sont effectuées et les résultats montrent qu’il serait possible de faire fonctionner, conformément au besoin étudié, un essaim de cent quadrirotors avec l’algorithme proposé. En particulier, l’essaim est capable de suivre le meneur, de maintenir la connectivité, d’éviter les collisions entre agents, d’éviter les obstacles et même de se faufiler dans des espaces étroits.----------ABSTRACT The ever-growing hardware capabilities and the rapid development of robotic control and navigation technologies have led us to consider the control of an entire swarm of quadrotors. Drone-based solutions have been developed for different applications: forest inventory, coastal management, traÿc monitoring, etc... Among these, the Search And Rescue application represents for us a very promising field of application and constitutes the first motivation of our work. As a result, a wide literature review on the matter is provided. Nevertheless, this work focuses on the swarm control itself, and not on the end user application. First, a mathematical model of the quadrotor dynamics is presented and several digital control laws are designed. The latter provide operating modes useful for the navigation algorithms, namely: velocity control, position control and tracking control. Then, two original and complimentary swarming solutions are proposed. On the one hand, a swarming algorithm for outdoor navigation is developed. Unlike most of the works reviewed in the literature, our solution handles not only the maintenance but also the initialization of the formation. More specifically, an hexagonal formation pattern is intro-duced. Then, positions are optimally assigned using the Hungarian algorithm. Finally, the agents move to their assigned position while avoiding collisions with the other fleet members thanks to a navigation algorithm inspired from Artificial Potential Field. In addition, this solution accounts for realistic design constraints and was successfully integrated into already existing quadrotor onboard software. Software-In-The-Loop simulation results are provided. On the other hand, a swarming solution for indoor navigation is investigated. The proposed algorithm enforces a certain set of expected individual simple behaviors such that a large swarm can follow a leader through cluttered environments relying only on local information. Preliminary simulations are run and the results show that it is possible to operate a swarm of a hundred quadrotors with the proposed algorithm. In particular, the swarm is able to follow the leader, maintain connectivity, avoid collisions with the other agents, avoid obstacles, and even squeeze to pass through narrow spaces

Formation control of nonholonomic mobile robots: the virtual structure approach

PhDIn recent years, there has been a considerable growth in applications of multi-robot systems as opposed to single-robot systems. This thesis presents our proposed solutions to a formation control problem in which mobile robots are required to create a desired formation shape and track a desired trajectory as a whole. In the first instance, we study the formation control problem for unicycle mobile robots. We propose two control algorithms based on a cascaded approach: one based on a kinematic model of a robot and the other based on a dynamic model. We also propose a saturated controller in which actuator limitations are explicitly accounted for. To demonstrate how the control algorithms work, we present an extensive simulation and experimental study. Thereafter we move on to formation control algorithms in which the coordination error is explicitly defined. Thus, we are able to give conditions for robots keeping their desired formation shape without necessarily tracking the desired trajectory. We also introduce a controller in which both trajectory tracking and formation shape maintenance are achieved as well as a saturated algorithm. We validate the applicability of the introduced controllers in simulations and experiments. Lastly, we study the formation control problem for car-like robots. In this case we develop a controller using the backstepping technique. We give conditions for robots keeping their desired formation shape while failing to track their desired trajectories and present simulation results to demonstrate the applicability of the proposed controlle

Distributed constrained connectivity control for proximity networks based on a receding horizon scheme

info:eu-repo/semantics/publishe