Allowable Sampling Period for High-Order Multi-Agent Systems

This paper studies data-sampled high-order multi-agent systems over random networks. Dynamic output feedback protocols are applied to solve the consensus problem. It is revealed that the solvability of the consensus depends on the sampling period of the network. If the sampling period is too large, the consensus problem may be unsolvable. When the sampling period is sufficient small, it is shown that the mean square consensus can be achieved if the mean topology has globally reachable nodes and the protocol parameters simultaneously stabilize n-1 subsystems. By using the hybrid dynamical system theory, an allowable upper bound of sampling period is further provided.