Koopman autoencoders with attention-free latent memory and online change-point re-encoding reduce long-horizon error on Duffing, Repressilator, and IRMA benchmarks while keeping low latency.
(eds.): The Koopman Operator in Systems and Control
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Koopman models identified via meta-heuristic EDMD from engine simulations enable an adaptive MPC with disturbance observer and a feedback linearization controller that achieve comparable steady-state performance with the adaptive version showing superior robustness under varying conditions.
citing papers explorer
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Learning the Koopman Operator using Attention Free Transformers
Koopman autoencoders with attention-free latent memory and online change-point re-encoding reduce long-horizon error on Duffing, Repressilator, and IRMA benchmarks while keeping low latency.
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Koopman-Based Nonlinear Identification and Adaptive Control of a Turbofan Engine
Koopman models identified via meta-heuristic EDMD from engine simulations enable an adaptive MPC with disturbance observer and a feedback linearization controller that achieve comparable steady-state performance with the adaptive version showing superior robustness under varying conditions.