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This article mainly considers the bipartite containment control problem of multi-agent systems with first- and second-order dynamics, where the antagonistic networks and multiple leader groups are considered. Specially, under the antagonistic networks, the multiple leader groups constitute two opposite convex hulls. One is a real convex hull composed of the real leader groups and the other is a virtual convex hull composed of opposite virtual leaders. For the first-order multi-agent systems with multiple leader groups, the followers move into the stationary real or virtual convex hull. While for the second-order multi-agent systems, the followers finally move into the dynamic real or virtual convex hull. In both cases, we obtain the sufficient conditions on achieving bipartite containment control. In the end, the effectiveness is verified by some simulations. [ABSTRACT FROM AUTHOR]

In this paper, we study the consensus problem for a class of linear multiagent systems, where the communication networks are directed. First, a dynamic event-triggering mechanism is introduced, including some existing static event-triggering mechanisms as its special cases. Second, based on the dynamic event-triggering mechanism, a distributed control protocol is developed, which ensures that all agents can reach consensus with an exponential convergence rate. Third, it is shown that, with the dynamic event-triggering mechanism, the minimum interevent time between any two consecutive triggering instants can be prolonged and no agent exhibits Zeno behavior. Finally, an algorithm is provided to avoid continuous communication when the dynamic event-triggering mechanism is implemented. The effectiveness of the results is confirmed through a numerical example. [ABSTRACT FROM AUTHOR]

In this paper, we address the consensus problem for double-integrator multi-agent systems integrated with a novel reset control protocol. It reveals the conditions under which consensus is achieved and the reset function is in action. The proposed reset control essentially provides a dynamically generated higher gain for better transient consensus performance, including faster convergence with less control effort. Compared with a static high gain controller, this dynamic high gain mechanism is more efficient and sophisticated especially in regularly resetting the additional gain to zero during the dynamic evolution. [ABSTRACT FROM AUTHOR]