Defines a positivity certificate for finite-sample identifiability of the control-channel block in Koopman EDMDc and derives closed-loop statistical bounds under behavior policies.
Active learning of dynamics for data-driven control using koopman operators
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ASACK provides a unified online adaptation method for Koopman models of uncertain nonlinear systems that combines contractive learning laws, active excitation, and robust MPC safety bounds.
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Control-Channel Informativity for Koopman EDMDc under Behavior-Policy Data
Defines a positivity certificate for finite-sample identifiability of the control-channel block in Koopman EDMDc and derives closed-loop statistical bounds under behavior policies.
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ASACK : Adaptive Safe Active Continual Koopman Learning for Uncertain Systems with Contractive Guarantees
ASACK provides a unified online adaptation method for Koopman models of uncertain nonlinear systems that combines contractive learning laws, active excitation, and robust MPC safety bounds.