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Found 2 papers, 1 papers with code
Unconstrained learning of networked nonlinear systems via free parametrization of stable interconnected operators
Further, we can embed prior knowledge about the interconnection topology and stability properties of the system directly into the large-scale distributed operator we design.
Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology
In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met.
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