Event‐triggered consensus of Markovian jumping multi‐agent systems via stochastic sampling
Aihua Hu, Jinde Cao, Manfeng Hu, Liuxiao Guo · IET Control Theory and Applications · 2015
This study investigates the issue of mean square consensus for multiple agents connected by a directed network. The graph of the network is supposed to have a spanning tree and each agent is taken as a Markovian jumping system. By utilising the event‐triggered strategy, some sufficient conditions for consensus are presented whether the transition rates for the Markov chain being completely known or not. Furthermore, the event‐triggered function designed in this study is dependent on the stochastic sampled‐data from neighbouring agents. Theoretical results are provided according to the graph theory, Lyapunov functional and linear matrix inequality approach. Finally, a numerical example is given to demonstrate the effectiveness of the theoretical analysis.