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Stochastic Approximation Approach for Consensus and Convergence Rate Analysis of Multiagent Systems

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3 Author(s)
Juanjuan Xu ; School of Control Science and Engineering, Shandong University, Jinan, P.R.China ; Huanshui Zhang ; Lihua Xie

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.

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IEEE Transactions on Automatic Control  (Volume:57 ,  Issue: 12 )