Consensus of Multi-Agent Systems with Intermittent Communications via Sampling Time Unit Approach

Publication date: Available online 19 February 2020Source: NeurocomputingAuthor(s): Jian Sun, Zhanshan WangAbstractThis paper investigates the consensus problem of multi-agent systems with intermittent communications under sampled-data control. A novel approach called sampling time unit (STU) approach is proposed to study such system. In such approach, the work time is described by finite number of sampling time units and the rest time is describe by several average time units. The lengths of work time and rest time depend on the convergence or divergence property of each time unit. Based on the STU approach, the stabilization property at transition instants can be derived, which can compensate the divergence during rest time to some extents. The designed control scheme can tolerate a relatively large rest time. Based on the STU approach, a corresponding sampling-dependent time-varying Lyapunov function (SDTVLF) is utilized to describe the system state and derive the computable conditions for the overall consensus with maximum admissible rest time. Finally, a numerical example with two cases is provided to illustrate the feasibility of the theoretical results.
Source: Neurocomputing - Category: Neuroscience Source Type: research