Distributed System Identification for Linear Stochastic Systems with Binary Sensors
Abstract
The problem of distributed identification of linear stochastic system with unknown coefficients over time-varying networks is considered. For estimating the unknown coefficients, each agent in the network can only access the input and the binary-valued output of the local system. Compared with the existing works on distributed optimization and estimation, the binary-valued local output observation considered in the paper makes the problem challenging. By assuming that the agent in the network can communicate with its adjacent neighbours, a stochastic approximation based distributed identification algorithm is proposed, and the consensus and convergence of the estimates are established. Finally, a numerical example is given showing that the simulation results are consistent with the theoretical analysis.
Cite
@article{arxiv.2108.01488,
title = {Distributed System Identification for Linear Stochastic Systems with Binary Sensors},
author = {Kewei Fu and Han-Fu Chen and Wenxiao Zhao},
journal= {arXiv preprint arXiv:2108.01488},
year = {2021}
}