7 research outputs found

    An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination

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    This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations

    Distributed estimation over a low-cost sensor network: a review of state-of-the-art

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    Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked systems enable the employment of multiple sensors. Distributed estimation provides a scalable and fault-robust fusion framework with a peer-to-peer communication architecture. For this reason, there seems to be a real need for a critical review of existing and, more importantly, recent advances in the domain of distributed estimation over a low-cost sensor network. This paper presents a comprehensive review of the state-of-the-art solutions in this research area, exploring their characteristics, advantages, and challenging issues. Additionally, several open problems and future avenues of research are highlighted

    Optimal control approaches for consensus and path planning in multi-agent systems

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    Optimal control is one of the most powerful, important and advantageous topics in control engineering. The two challenges in every optimal control problem are defining the proper cost function and obtaining the best method to minimize it. In this study, innovative optimal control approaches are developed to solve the two problems of consensus and path planning in multi-agent systems (MASs). The consensus problem for general Linear-Time Invariant systems is solved by implementing an inverse optimal control approach which enables us to start by deriving a control law based on the stability and optimality condition and then according to the derived control define the cost function. We will see that this method in which the cost function is not specified a priori as the conventional optimal control design has the benefit that the resulting control law is guaranteed to be both stabilizing and optimal. Three new theorems in related linear algebra are developed to enable us to use the algorithm for all the general LTI systems. The designed optimal control is distributed and only needs local neighbor-to-neighbor information based on the communication topology to make the agents achieve consensus and track a desired trajectory. Path planning problem is solved for a group are Unmanned Aerial Vehicles (UAVs) that are assigned to track the fronts of a fires in a process of wildfire management. We use Partially Observable Markov Decision Process (POMDP) in order to minimize the cost function that is defined according to the tracking error. Here the challenge is designing the algorithm such that (1) the UAVs are able to make decisions autonomously on which fire front to track and (2) they are able to track the fire fronts which evolve over time in random directions. We will see that by defining proper models, the designed algorithms provides real-time calculation of control variables which enables the UAVs to track the fronts and find their way autonomously. Furthermore, by implementing Nominal Belief-state Optimization (NBO) method, the dynamic constraints of the UAVs is considered and challenges such as collision avoidance is addressed completely in the context of POMDP

    Content Modification Attacks on Networked Robotic Systems

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    With the advent of communication networks in robotic systems, distributed networked robotic systems can be deployed to perform certain tasks collaboratively. However, this makes the networked robotic systems vulnerable to cyber attacks. Thus, the rigorous study of the impact of cyber attacks and the development of corresponding defense mechanisms are necessary. In this dissertation, the cyber-physical security issue of networked robotic systems is studied under a specific type of cyber attack called content modification attack, which can modify the data content transmitted in the communication networks among the robots. Specifically, algorithms for attack design and detection for content modification attacks are studied. The physics of the robotic system is utilized to design and detect the cyber attacks for networked robotic systems. Content modification attacks are studied for the synchronization problem in networked robotic systems. The considered systems include multi-robot systems, bilateral teleoperation systems and bilateral tele-driving systems. To demonstrate the potential severity of the attack, a constructive methodology for attack design is also developed. Specifically, a destabilizing content modification attack referred to as a malignant content modification attack (MCoMA) is designed based on the system storage function, which can lead to system instability and even physical system damage. To protect the system, a physics-based attack detection scheme with an encoding-decoding structure is proposed for general content modification attacks. As part of the tele-driving system study, a novel passivity-based adaptive bilateral tele-driving control scheme is also proposed in the presence of network delays and dynamics parametric uncertainties. Simulations and experiments have also been conducted to validate the proposed algorithms. This study demonstrates the potential of utilizing the physics of the robotic system to better understand and strengthen the security of the networked robotic systems

    Commande des Systèmes Multi-agent d'Ordre Fractionnaire

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    This thesis focuses on the distributed coordination of fractional-order multi-agent systems under fixed directed communication graph. Firstly, formation producing with absolute damping and communication delay of fractional-order multi-agent systems is studied. A control law is proposed and some sufficient conditions are derived for achieving formation producing. However, in some scenarios, it might be desirable that all agents achieve formation and move as a group, instead of rendezvous at a stationary point. Therefore, secondly, formation producing with relative damping and communication delay is considered. Thirdly, consensus tracking of fractional-order multi-agent systems with a time-varying reference state is studied. A common control law and a control law based on error predictor are proposed, and it is shown that the control laws are effective when a communication graph has directed spanning trees. Meanwhile, it is proved that the convergence of systems is faster using the control law based on error predictor than by the common one. Finally, the above control laws are extended to achieve formation-tracking problems. In fact, in many cases information can be sent from a reference state to only its neighbor agents not to all the agents. In order to solve the above problem, an effective control law is given to achieve consensus with a constant reference state. Then, an effective general control law and an effective particular one are proposed to achieve consensus with a time-varying reference state. Furthermore, the above control laws are extended to achieve the formation tracking problemsCe travail concerne la commande des systèmes multi-agent d’ordre fractionnaire utilisant une topologie de communication fixe. Premièrement, la production en formation avec atténuation absolue et retard de communication est étudiée. Pour cela, une loi de commande et des conditions suffisantes sont proposées. Toutefois, dans certains scénarios, il est souhaitable que tous les agents atteignent la formation souhaitée tout en se déplacent en groupe, au lieu d’un rendez-vous à un point fixe. Ce cas sera traité en étudiant la production en formation avec atténuation relative et retard de communication. Troisièmement, la poursuite par consensus des systèmes avec un état de référence variable dans le temps est étudiée. Une loi de commande commune et une seconde basée sur la prédiction d’erreur sont proposées, et le problème du consensus est résolu quand le graphe de communication contient un arbre dirigé. Il a été prouvé que la convergence du système est plus rapide en utilisant la loi basée sur la prédiction d’erreur plutôt que celle de commande commune. Enfin, les lois de commande ci-dessus sont étendues au cas de la poursuite en formation. En effet, dans de nombreux cas, l'information peut être envoyée à partir d'un état de référence vers les agents voisins uniquement et non pas à l’ensemble des agents. Afin de résoudre ce problème, une loi de commande est proposée afin de résoudre le problème du consensus avec un état de référence constant. Puis, deux lois de commande sont proposées afin de résoudre le problème du consensus avec un état de référence variant dans le temps. Ces lois sont étendues pour résoudre le problème de la poursuite en formatio

    On Iterative Learning in Multi-agent Systems Coordination and Control

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    Ph.DDOCTOR OF PHILOSOPH

    Texas Law Review

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    Journal containing articles, notes, book reviews, and other analyses of law and legal cases
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