Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99108
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Title: A distributed stochastic approximation algorithm for stochastic LQ control with unknown uncertainty
Authors: Zhang, Z
Xu, J
Li, X 
Issue Date: May-2023
Source: Automatica, May 2023, v. 151, 110917
Abstract: This paper studies a discrete-time stochastic control problem with linear quadratic criteria over an infinite-time horizon. We focus on control systems whose system matrices are associated with random parameters involving unknown statistical properties. We design a distributed stochastic approximation algorithm to tackle the Riccati equation and derive the optimal controller stabilizing the system. The convergence analysis is provided.
Keywords: Distributed stochastic approximation
Stochastic control
Multiplicative noise
Unknown statistics
Publisher: Pergamon Press
Journal: Automatica 
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2023.110917
Rights: © 2023 Elsevier Ltd. All rights reserved.
© 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Zhang, Z., Xu, J., & Li, X. (2023). A distributed stochastic approximation algorithm for stochastic LQ control with unknown uncertainty. Automatica, 151, 110917 is available at https://doi.org/10.1016/j.automatica.2023.110917.
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