4,036 research outputs found
Designing Fully Distributed Consensus Protocols for Linear Multi-agent Systems with Directed Graphs
This paper addresses the distributed consensus protocol design problem for
multi-agent systems with general linear dynamics and directed communication
graphs. Existing works usually design consensus protocols using the smallest
real part of the nonzero eigenvalues of the Laplacian matrix associated with
the communication graph, which however is global information. In this paper,
based on only the agent dynamics and the relative states of neighboring agents,
a distributed adaptive consensus protocol is designed to achieve
leader-follower consensus for any communication graph containing a directed
spanning tree with the leader as the root node. The proposed adaptive protocol
is independent of any global information of the communication graph and thereby
is fully distributed. Extensions to the case with multiple leaders are further
studied.Comment: 16 page, 3 figures. To appear in IEEE Transactions on Automatic
Contro
Differential Inequalities in Multi-Agent Coordination and Opinion Dynamics Modeling
Distributed algorithms of multi-agent coordination have attracted substantial
attention from the research community; the simplest and most thoroughly studied
of them are consensus protocols in the form of differential or difference
equations over general time-varying weighted graphs. These graphs are usually
characterized algebraically by their associated Laplacian matrices. Network
algorithms with similar algebraic graph theoretic structures, called being of
Laplacian-type in this paper, also arise in other related multi-agent control
problems, such as aggregation and containment control, target surrounding,
distributed optimization and modeling of opinion evolution in social groups. In
spite of their similarities, each of such algorithms has often been studied
using separate mathematical techniques. In this paper, a novel approach is
offered, allowing a unified and elegant way to examine many Laplacian-type
algorithms for multi-agent coordination. This approach is based on the analysis
of some differential or difference inequalities that have to be satisfied by
the some "outputs" of the agents (e.g. the distances to the desired set in
aggregation problems). Although such inequalities may have many unbounded
solutions, under natural graphic connectivity conditions all their bounded
solutions converge (and even reach consensus), entailing the convergence of the
corresponding distributed algorithms. In the theory of differential equations
the absence of bounded non-convergent solutions is referred to as the
equation's dichotomy. In this paper, we establish the dichotomy criteria of
Laplacian-type differential and difference inequalities and show that these
criteria enable one to extend a number of recent results, concerned with
Laplacian-type algorithms for multi-agent coordination and modeling opinion
formation in social groups.Comment: accepted to Automatic
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