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Found 4 papers, 4 papers with code
Distributed Optimal Control of Graph Symmetric Systems via Graph Filters
Designing distributed optimal controllers subject to communication constraints is a difficult problem unless structural assumptions are imposed on the underlying dynamics and information exchange structure, e. g., sparsity, delay, or spatial invariance.
Toward Certified Robustness Against Real-World Distribution Shifts
We consider the problem of certifying the robustness of deep neural networks against real-world distribution shifts.
Data-driven Distributed and Localized Model Predictive Control
By imposing locality constraints on the system response, we show that the amount of data needed for our synthesis problem is independent of the size of the global system.
Communication Topology Co-Design in Graph Recurrent Neural Network Based Distributed Control
Our proposed parameterization enjoys a local and distributed architecture, similar to previous Graph Neural Network (GNN)-based parameterizations, while further naturally allowing for joint optimization of the distributed controller and communication topology needed to implement it.
