Research article

Multi-leader-follower group consensus of stochastic time-delay multi-agent systems subject to Markov switching topology


  • Received: 23 March 2022 Revised: 13 May 2022 Accepted: 16 May 2022 Published: 20 May 2022
  • The multi-leader-follower group consensus issue of a class of stochastic time-delay multi-agent systems subject to Markov switching topology is investigated. The purpose is to determine a distributed control protocol to make sure that the followers' states converge in mean square to a convex hull generated by the leaders' states. Through a model transformation, the problem is transformed into a mean-square stability issue of a new system. Then, an easy-to-check sufficient condition for the solvability of the multi-leader-follower group consensus issue is proposed by utilizing the Lyapunov stability theory, graph theory, as well as several inequality techniques. It is shown that the required feedback gain can be acquired once the condition is satisfied. Finally, an example is used to illustrate the effectiveness of the control protocol.

    Citation: Tong Guo, Jing Han, Cancan Zhou, Jianping Zhou. Multi-leader-follower group consensus of stochastic time-delay multi-agent systems subject to Markov switching topology[J]. Mathematical Biosciences and Engineering, 2022, 19(8): 7504-7520. doi: 10.3934/mbe.2022353

    Related Papers:

  • The multi-leader-follower group consensus issue of a class of stochastic time-delay multi-agent systems subject to Markov switching topology is investigated. The purpose is to determine a distributed control protocol to make sure that the followers' states converge in mean square to a convex hull generated by the leaders' states. Through a model transformation, the problem is transformed into a mean-square stability issue of a new system. Then, an easy-to-check sufficient condition for the solvability of the multi-leader-follower group consensus issue is proposed by utilizing the Lyapunov stability theory, graph theory, as well as several inequality techniques. It is shown that the required feedback gain can be acquired once the condition is satisfied. Finally, an example is used to illustrate the effectiveness of the control protocol.



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