Quantized Consensus of Multi-Agent Networks With Sampled Data and Markovian Interaction Links
研究了量化、采样数据和马尔可夫交互链路对领导者跟随多智能体网络一致性的联合影响，给出了保证均方意义下一致性跟踪的充要条件。
This paper investigates the joint effect of quantization, sampled data, and general Markovian interaction links on consensus networks with a leader under directed graphs. The diversity of edges formed by all the followers and the leader is also considered. Each agent in the network possesses continuous-time general linear dynamics. Each agent's state is measured only at sampling time instants, which is encoded before transmission. Subsequently, the encoded state is transmitted through noiseless digital communication links with Markovian switching rates. For this problem, a sufficient condition is derived to guarantee the convergence of the encoded states, based on which a necessary and sufficient condition is obtained to achieve consensus tracking in the mean-square sense. In addition, two sufficient conditions on coupling gain, one of which is fully distributed, are provided by proposing an optimal linear quadratic regulator-based gain matrix to ensure consensus tracking and then, the analysis of consensus region is presented. Finally, a numerical example is presented for illustrating the effectiveness of the theoretical results.