2019•Unpublished venueRequires access

Adaptive Consensus Control for Nonlinear Multi-agent Systems with Unknown Control Directions

Qingling Wang, Yajun Zheng, Changyin Sun

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Abstract

This paper investigates the adaptive leaderless consensus of first-order agents with unknown control directions under switching topologies. The unknown control directions can be nonidentical and the network topologies are switching but jointly connected topologies in the sense that the union of the associated graphs over a certain time interval always has a spanning tree. It is shown that the leaderless consensus problem can be solved if the distributed control algorithms are properly designed. Finally, one example is given to show the effectiveness of the proposed algorithms.

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What this paper is about

This paper investigates the adaptive leaderless consensus of first-order agents with unknown control directions under switching topologies. The unknown control directions can be nonidentical and the network topologies are switching but jointly connected topologies in the sense that the union of the associated graphs over a certain time interval always has a spanning tree. It is shown that the leaderless consensus problem can be solved if the distributed control algorithms are properly designed. Finally, one example is given to show the effectiveness of the proposed algorithms.

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Available abstract

This paper investigates the adaptive leaderless consensus of first-order agents with unknown control directions under switching topologies. The unknown control directions can be nonidentical and the network topologies are switching but jointly connected topologies in the sense that the union of the associated graphs over a certain time interval always has a spanning tree. It is shown that the leaderless consensus problem can be solved if the distributed control algorithms are properly designed. Finally, one example is given to show the effectiveness of the proposed algorithms.

Key concepts: Network topology, Consensus, Multi-agent system, Computer science, Nonlinear system, Control (management), Adaptive control, Spanning tree

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