Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems
Date of Issue2012
School of Electrical and Electronic Engineering
In this note, we study the consensus problem for multiagent systems with measurement noises. Different from the existing approach, the consensus problem is converted to a root finding problem for which the stochastic approximation theory can be applied. By choosing an appropriate regression function, we propose a consensus algorithm which is applicable to systems with more general measurement noise processes, including stationary autoregressive and moving average (ARMA) processes and infinite moving average (MA) processes. Further, we establish a relationship between the convergence rate and the exponent of the step size of the algorithm. Particularly, strong convergence rate for systems with a leader-follower topology is studied.
DRNTU::Engineering::Electrical and electronic engineering
IEEE transactions on automatic control
© 2012 IEEE.