A decoupled designing approach for sampling consensus of multi-agent systems

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)310-325
Journal / PublicationInternational Journal of Robust and Nonlinear Control
Issue number1
Online published29 Jun 2017
Publication statusPublished - 10 Jan 2018


This paper introduces the motion-planning approaches to solve the distributed consensus problems via sampling measurements. First, for first-order multiagent systems, a class of sampled-data–based algorithms are developed with arbitrary sampling periods, which solve the asymptotic consensus problem under both directed fixed and random switching topologies. Then, a new kind of distributed consensus algorithms is designed based on sampling measurements for second-order multiagent systems. Under both the directed fixed and periodical switching topologies, asymptotic consensus problems of second-order multiagent systems can be solved by using the proposed algorithms. Compared with existing continuous-time consensus algorithms, one of remarkable advantages of proposed algorithms is that the sampling periods, communication topologies, and control gains are decoupled and can be separately designed, which relaxes many restrictions in controller designs. Finally, some numerical examples are given to illustrate the effectiveness of the analytical results.

Research Area(s)

  • directed spanning tree, distributed consensus, motion-planning approach, sampling measurement