Consensus analysis of multi-agent systems with general linear dynamics and switching topologies by non-monotonically decreasing Lyapunov function

Abstract

This paper investigates consensus problems for multi-agent systems with general linear dynamics and switching topologies. In order to deal with the intricate interaction between dynamics of isolated agents and switching-disconnected topologies, the consensus analysis is performed by nonmonotonically decreasing Lyapunov function. Particularly, the design of consensus laws is explored from the perspective of fast time-varying systems with two time scales. Sufficient conditions for achieving consensus are derived, which depend on not only feedback gains and connectivity of network topologies but also the speed of topology switching and the stability of individual agent. Therefore consensus laws are generalized in the sense that the dynamics of linear agents are allowed to be unstable and switching topologies are allowed to be jointly weakly connected and balanced. Finally, numerical simulations are provided to demonstrate the effectiveness of theoretical results. ARTICLE HISTORY

Stabilization of piecewise-homogeneous Markovian switching CVNNs with mode-dependent delays and incomplete transition rates

“…Such a situation motivates our present research. It should be noted that, so far, Markovian switching systems (MSSs) have witnessed a significant progress due to the fact that MSS can describe the random abrupt changes and the environmental variance, which might be governed by a Markovian process or Markovian chain with finite modes (Liu et al, 2018;Luo et al, 2020;Ma et al, 2018;Zhang et al, 2019). During the past years, a great many of relevant results for Markovian switching neural networks (MSNNs) with time delays have been introduced (Nagamani et al, 2017;Zhang et al, 2015;T.…”