4.7 Article

Consensus of One-Sided Lipschitz Multiagents Under Switching Topologies

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2019.2897775

关键词

Topology; Switches; Protocols; Nonlinear dynamical systems; Network topology; Symmetric matrices; Leader-following consensus; multiagents; one-sided Lipschitz systems; switching topology

资金

  1. National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning [NRF-2017R1A1A1A05001325]
  2. Brain Korea 21 Plus Project

向作者/读者索取更多资源

This paper focuses on leader-following consensus of multiagents with one-sided Lipschitz nonlinear dynamics under switching topologies and consensus control strategies. A new condition for consensus is established through dwell time constraints and communication restoration mechanisms. Simplified consensus controller design conditions are developed and consensus protocol gains can be obtained directly through convex routines. An algorithm using cone complementary linearization approach is also provided for solving nonlinear constraints in a numerical simulation demonstrating the efficiency of the proposed control schemes for multiagents.
This paper considers the leader-following consensus of multiagents with one-sided Lipschitz nonlinear dynamics by considering switching topologies. For the suitable selection of the consensus control gain matrix and coupling weight, a new condition for consensus is achieved for switching communication links with a directed spanning tree in the topology by constraining the dwell time. Employing a communication restoration mechanism allows a method to be obtained for the case in which a topology violates a permanent directed spanning tree. Computationally straightforward consensus controller design conditions that are necessary and sufficient for the former conditions are also developed for both cases. These simpler conditions can be used to obtain consensus protocol gains directly through convex routines. An algorithm is also provided to solve nonlinear constraints using the cone complementary linearization approach by considering a nonlinear objective function optimization problem. A numerical simulation is provided for multiagents that demonstrates the proposed control schemes' efficiency.

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