Finite-time Consensus for Multi-agent Systems with Application to Sensor Fusion

This paper studies the finite-time consensus for a group of dynamic agents.For the entire group,we establish the explicit expression of the consensus state,which can be characterized by the new concept of weighted average consensus with respect to a monotonic function.For networks with undirected topology,we prove that the weighted average consensus with respect to a monotonic function can be solved in finite time when the interactions among agents are taken as power-law based function.These results are further extended to a class of networks where the topologies are directed and satisfy a detailed balance condition on coupling weights.As an application of the theoretical results to sensor fusion,we propose a distributed scheme to compute the maximum-likelihood(ML) estimate of unknown parameters.Numerical simulations show that the distributed scheme can be used to compute the ML estimate of unknown parameters effectively.This paper studies the finite-time consensus for a group of dynamic agents.For the entire group,we establish the explicit expression of the consensus state,which can be characterized by the new concept of weighted average consensus with respect to a monotonic function.For networks with undirected topology,we prove that the weighted average consensus with respect to a monotonic function can be solved in finite time when the interactions among agents are taken as power-law based function.These results are fuIEEE Control Systems Society(CSS)、中国自动化学会控制理论专业委员会