Bipartite Consensus for Multi-agent Systems with Antagonistic Interactions and Communication Noise over Lossy Wireless Networks

We consider the bipartite consensus for discrete-time multi-agent systems with communication noise and antagonistic interactions over wireless networks, where the network is vulnerable to signal lossy. In this paper, we first simulate lossy wireless networks as a ergodic Markov chain. Based on stochastic approximation technique, a bipartite consensus protocol for Markov lossy wireless network is employed, where a time-varying gain is used to weaken the negative impact of the communication noise. By doing so, we further show the mean square and almost surely bipartite consensus via a state space decomposition method. Last, a numerical example is given to support our new results.