In this paper, the bipartite consensus problem is addressed via adaptive event-triggered control for multi-agent systems in directed communication networks, where cooperative and competitive interactions are considered simultaneously. Under a strongly connected digraph, a novel fully distributed control protocol is first put forward, which consists of an adaptive controller and two event-triggered mechanisms. The protocol is flexible and capable of achieving bipartite consensus without employing global information. Meanwhile, the Zeno behavior cannot occur by embedding L p functions in the event-triggered mechanisms. Furthermore, a general digraph with a spanning tree is investigated, and it is shown that the proposed protocol is still effective in bipartite consensus including the leader-follower one as a special case. It is worth noting that there is no need for the protocol to continuously update the controller, nor to maintain the uninterrupted communication with neighbors. Finally, the validity of the presented results is confirmed by simulations.

This article focuses on the distributed consensus control problem for nonlinear multi‐agent systems subject to sensor uncertainty. To be specific, we study nonlinear multi‐agent systems of lower or upper triangular structure with unknown growth rate and sensor uncertainty. A new time‐varying gain approach is proposed to construct observers as well as distributed output‐feedback controllers. By selecting suitable design parameters, the leader‐follower consensus of nonlinear multi‐agent systems is achieved. Different from the existing results, a time‐varying function in a logarithmic form is introduced to deal with unknown growth rate. Moreover, a monotonically increasing time‐varying function is constructed to cope with uncertain sensor sensitivity. Two simulation examples are provided to demonstrate the effectiveness of the proposed distributed consensus control algorithms.

This paper investigates the synchronization of reaction-diffusion neural networks (RDNNs) with distributed delay via quantized boundary control. To reduce the communication burden, a novel control strategy combined boundary control and logarithmic quantizer is proposed, and two controllers respectively subject to constant and adaptive coefficients are carried out. Worth mentioning that the adaptive feedback gain is a matrix in this paper rather than a one-dimensional variable in most of the existing literatures. Using the Lyapunov functional, the sufficient conditions for delay-dependent synchronization are obtained through linear matrix inequalities. The effectiveness of the proposed control strategy is illustrated via two examples.

This article concentrates on the sampled-data secure bipartite consensus problem for a class of nonlinear multiagent systems under intermittent denial-of-service attacks. The network communication channels are destroyed when the attacks occur, which causes all the system states to be unavailable. A novel distributed sampled-data output feedback control protocol is developed by using the discontinuous sensor data. It is proved by the Lyapunov stability analysis that the considered nonlinear multiagent systems can achieve bipartite consensus exponentially in light of the designed control protocol. Then, the control algorithm is extended to systems with both state and input delay. Finally, a simulation example is presented to verify the effectiveness of the proposed control protocol.

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