This paper presents a novel solution for the discrete time dynamic average consensus problem. Given a set of time-varying input signals over the nodes of an undirected graph, the proposed algorithm tracks, at each node, the input signals’ average. The algorithm is based on a sequence of consensus stages combined with a second order diffusive protocol. The former overcomes the need of k-th order differences of the inputs and conservation of the network state average, while the latter overcomes the trade-off between speed and accuracy of the consensus stages by just storing the previous estimate at each node. The result is a protocol that is fast, arbitrarily accurate, and robust against input noises and initializations. The protocol is extended to an asynchronous and randomized version that follows a gossiping scheme that is robust against potential delays and packet losses. We study the convergence properties of the algorithms and validate them via simulations.

Sebastian, E., Montijano, E., Sagues, C., Franceschelli, M., Gasparri, A. (2023). Accelerated Multi-Stage Discrete Time Dynamic Average Consensus. IEEE CONTROL SYSTEMS LETTERS, 1-1 [10.1109/LCSYS.2023.3289483].

Accelerated Multi-Stage Discrete Time Dynamic Average Consensus

Gasparri A.
2023-01-01

Abstract

This paper presents a novel solution for the discrete time dynamic average consensus problem. Given a set of time-varying input signals over the nodes of an undirected graph, the proposed algorithm tracks, at each node, the input signals’ average. The algorithm is based on a sequence of consensus stages combined with a second order diffusive protocol. The former overcomes the need of k-th order differences of the inputs and conservation of the network state average, while the latter overcomes the trade-off between speed and accuracy of the consensus stages by just storing the previous estimate at each node. The result is a protocol that is fast, arbitrarily accurate, and robust against input noises and initializations. The protocol is extended to an asynchronous and randomized version that follows a gossiping scheme that is robust against potential delays and packet losses. We study the convergence properties of the algorithms and validate them via simulations.
2023
Sebastian, E., Montijano, E., Sagues, C., Franceschelli, M., Gasparri, A. (2023). Accelerated Multi-Stage Discrete Time Dynamic Average Consensus. IEEE CONTROL SYSTEMS LETTERS, 1-1 [10.1109/LCSYS.2023.3289483].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/445688
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