Consensus Analysis Based on Impulsive Systems in Multiagent Networks

Abstract

This paper discusses consensus problems for multiagent networks under directed communication graphs. The motions of agents are described by impulsive differential equations, and thus, consensus algorithms can be designed in terms of impulsive systems. Different from the standard consensus algorithms which rely on continuous-time or discrete-time models, the proposed algorithms based on impulsive systems take advantages of instantaneous information. It is shown that the proposed algorithms have a faster convergence speed than the standard consensus algorithms. Moreover, conditions under which all agents reach consensus with the desired performance are presented for the multiagent networks with external disturbances. Simulation results demonstrate the effectiveness of the proposed algorithms.