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Tags: control

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    Experiment

    Private An Inverse Learning Paradigm for Controller Tuning Rules

    A sim2real approach for data-driven controller tuning, utilizing a digital twin to generate input-output data and suitable controllers around nominal parameter values. It is a...
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    Experiment

    Private Toward eXplainabile Data-Driven Control (XDDC): The Property-Preserving Frame...

    As Artificial Intelligence (AI) techniques continue to advance, the need for explainability becomes increasingly crucial, especially in sensitive or safety-critical domains....
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    Experiment

    Private Meta-learning for model-reference data-driven control

    One-shot direct model-reference control design techniques, like the Virtual Reference Feedback Tuning (VRFT) approach, offer time-saving solutions for calibrating...