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Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching

  • Xiaotai WuEmail author
  • Yang Tang
  • Jinde Cao
  • Wenbing Zhang
Living reference work entry
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Abstract

In this chapter, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode’s switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is firstly proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

Keywords

Consensus Multi-agent systems Switched systems Asynchronous switching Comparison principle 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xiaotai Wu
    • 1
    Email author
  • Yang Tang
    • 2
  • Jinde Cao
    • 3
  • Wenbing Zhang
    • 4
  1. 1.The School of Mathematics and PhysicsAnhui Polytechnic UniversityWuhuChina
  2. 2.The Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of EducationEast China University of Science and TechnologyShanghaiChina
  3. 3.The Department of MathematicsSoutheast UniversityNanjingChina
  4. 4.The Department of MathematicsYangzhou UniversityYangzhouChina

Section editors and affiliations

  • Yang Tang
    • 1
  1. 1.Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of EducationEast China University of Science and TechnologyShanghaiChina

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