A learned reduced-order feedback controller computes near-optimal distributed controls for parametrized PDEs in real time, with a latent loop that works even without online state measurements.
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Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models
A learned reduced-order feedback controller computes near-optimal distributed controls for parametrized PDEs in real time, with a latent loop that works even without online state measurements.