A data-driven method designs probabilistic finite L2-gain stabilizers for stochastic linear systems from noisy trajectories via LMIs.
Formulas for data-driven control: Stabilization, optimality, and robustness
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Introduces DeePConverters that apply data-enabled predictive control to achieve data-driven, optimal, robust, and adaptive operation of grid-connected power converters without relying on explicit grid models.
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Data-Driven Probabilistic Finite $\mathcal{L}_2$-Gain Stabilization of Stochastic Linear Systems
A data-driven method designs probabilistic finite L2-gain stabilizers for stochastic linear systems from noisy trajectories via LMIs.
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A Data-Driven Optimal Control Architecture for Grid-Connected Power Converters
Introduces DeePConverters that apply data-enabled predictive control to achieve data-driven, optimal, robust, and adaptive operation of grid-connected power converters without relying on explicit grid models.