Event-triggered bipartite consensus of multi-agent systems in signed networks

<abstract><p>This paper focuses on the event-triggered bipartite consensus of multi-agent systems in signed networks, where the dynamics of each agent is assumed to be Lur'e system, and both the cooperative interaction and antagonistic interaction are allowed among neighbor agents. A novel event-triggered communication scheme is presented to save limited network resources, and distributed bipartite control techniques are raised to address the bipartite leaderless consensus and bipartite leader-following consensus respectively. By virtue of the Lyapunov stability theory and algebraic graph theory, bipartite consensus conditions are derived, which can be easily solved by MATLAB. In addition, the upper bounds of the sampling period and triggered parameter can be estimated. Finally, two examples are employed to show the validity and advantage of the proposed transmission scheme.</p></abstract>

A novel bipartite consensus tracking scheme for unknown nonlinear multi-agent systems: Theoretical analysis and applications

This article proposes a novel distributed data-driven bipartite consensus tracking scheme for bipartite consensus tracking problems of multi-agent systems with bounded disturbances and coopetition networks. The proposed scheme only uses the input/output data of each agent without requiring the agents’ dynamics. We obtain the equivalent dynamic linearization data model for a controlled plant using the dynamic linearization technique based on the pseudo partial derivative. Considering the cooperative and competitive interactions among agents, the proposed method ensures that agents with adversarial relationships implement bipartite consensus tracking tasks even if only a subset of agents can access the information from the virtual leader. Moreover, the strict proof process of convergence properties reveals that the tracking error coverages to a small range around the origin. We also establish a set of software and hardware platform to demonstrate the effectiveness of the proposed distributed data-driven bipartite consensus tracking method.

Compensator-based periodically intermittent control for nonlinear second-order multi-agent systems

This article studies leader-following bipartite consensus control of a class of nonlinear second-order multi-agent systems. A new compensator-based periodically intermittent control algorithm is proposed for the second-order multi-agent systems. The compensator can be implemented in a fully distributed way. In other words, in order to construct the compensator for a certain agents, the values of measurement output of each agent and its neighbor agents are monitored for the construction of compensator. Considering the limited bandwidth of communication networks, the state variable of compensator is used by the controller for each follower to construct a novel periodically intermittent control algorithm, which can effectively reduce the communication frequency among agents in the control process. By combing stability theory and algebra graph theory, the criteria are obtained for the achievement of global exponential bipartite consensus under a fixed directed topology. Finally, some numerical examples are provided to illustrate the performance of the proposed control algorithm.