17,459 research outputs found
Persistence based analysis of consensus protocols for dynamic graph networks
This article deals with the consensus problem involving agents with
time-varying singularities in the dynamics or communication in undirected graph
networks. Existing results provide control laws which guarantee asymptotic
consensus. These results are based on the analysis of a system switching
between piecewise constant and time-invariant dynamics. This work introduces a
new analysis technique relying upon classical notions of persistence of
excitation to study the convergence properties of the time-varying multi-agent
dynamics. Since the individual edge weights pass through singularities and vary
with time, the closed-loop dynamics consists of a non-autonomous linear system.
Instead of simplifying to a piecewise continuous switched system as in
literature, smooth variations in edge weights are allowed, albeit assuming an
underlying persistence condition which characterizes sufficient inter-agent
communication to reach consensus. The consensus task is converted to
edge-agreement in order to study a stabilization problem to which classical
persistence based results apply. The new technique allows precise computation
of the rate of convergence to the consensus value.Comment: This article contains 7 pages and includes 4 figures. it is accepted
in 13th European Control Conferenc
Decentralized Event-Triggered Consensus of Linear Multi-agent Systems under Directed Graphs
An event-triggered control technique for consensus of multi-agent systems
with general linear dynamics is presented. This paper extends previous work to
consider agents that are connected using directed graphs. Additionally, the
approach shown here provides asymptotic consensus with guaranteed positive
inter-event time intervals. This event-triggered control method is also used in
the case where communication delays are present. For the communication delay
case we also show that the agents achieve consensus asymptotically and that,
for every agent, the time intervals between consecutive transmissions is
lower-bounded by a positive constant.Comment: 9 pages, 5 figures, A preliminary version of this manuscript has been
submitted to the 2015 American Control Conferenc
Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks
Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
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