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In this brief, the bipartite consensus problem of linear multi-agent systems with a dynamic event-triggered protocol is studied. A distributed controller with a cooperative-competitive mechanism and estimated states is first designed, and a dynamic event-triggered mechanism proposed in which the triggering threshold is dynamically updated by the designed auxiliary equation. Under this control strategy, the systems only need the states of the agent and neighboring agents at the triggering instants. At the same time, the estimator is considered to reduce the states deviation of multi-agent systems between adjacent triggering instants. Moreover, bipartite consensus can be achieved without Zeno behavior. Finally, the feasibility of the proposed method is illustrated in a unicycle model. [ABSTRACT FROM AUTHOR]

We consider the discrete-time distributed bipartite-consensus problem for multiagent systems subject to measurement noises and time-varying random networks, where the information exchange among the agents can be antagonistic and disturbed by both multiplicative and additive noises. The antagonistic information is characterized by a signed random graph. The main challenge is that the coexistence of multiplicative noise and antagonistic information does not allow the multiplicative noise term to be converted into an error equation. Based on the semi-decomposition method and Lyapunov-based technique, we derive sufficient conditions for stochastic approximation step size to assure the mean square bipartite consensus. Moreover, the convergence rate of the consensus error is explicitly formulated, which is tightly linked to the step size and the eigenvalues of the Laplacian matrix. Finally, we verify the main results via a numerical example. [ABSTRACT FROM AUTHOR]