Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems
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...
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sg-ntu-dr.10356-956162020-03-07T14:02:44Z Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems Xu, Juanjuan Zhang, Huanshui Xie, Lihua School of Electrical and Electronic Engineering DRNTU::Engineering::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. 2013-07-11T06:09:55Z 2019-12-06T19:18:17Z 2013-07-11T06:09:55Z 2019-12-06T19:18:17Z 2012 2012 Journal Article Xu, J., Zhang, H., & Xie, L. (2012). IEEE Transactions on Automatic Control, 57(12), 3163-3168. 0018-9286 https://hdl.handle.net/10356/95616 http://hdl.handle.net/10220/11203 10.1109/TAC.2012.2199175 en IEEE transactions on automatic control © 2012 IEEE. |
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DRNTU::Engineering::Electrical and electronic engineering Xu, Juanjuan Zhang, Huanshui Xie, Lihua Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
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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. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Xu, Juanjuan Zhang, Huanshui Xie, Lihua |
format |
Article |
author |
Xu, Juanjuan Zhang, Huanshui Xie, Lihua |
author_sort |
Xu, Juanjuan |
title |
Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
title_short |
Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
title_full |
Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
title_fullStr |
Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
title_full_unstemmed |
Stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
title_sort |
stochastic approximation approach for consensus and convergence rate analysis of multiagent systems |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/95616 http://hdl.handle.net/10220/11203 |
_version_ |
1681048804944510976 |