<ul><li>This paper presents a method for distributed optimal control for linear networked systems using graph recurrent neural networks (GRNNs).</li><li>The existing approaches for this problem result in centralized optimal controllers with offline training processes.</li><li>The main contribution of this work is the development of a distributed, online training approach for the optimal controllers.</li><li>The method is demonstrated through numerical simulations using a dedicated simulator.</li></ul>

Graph Neural Network-Based Distributed Optimal Control for Linear Networked Systems: An Online Distributed Training Approach

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