A unified data-driven co-design method for event-triggered and sparse control in noisy NCS with unknown dynamics, providing stability and H_infty conditions via iterative optimization.
Data informativity: A new perspective on data-driven analysis and control
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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math.OC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A new regularized covariance parameterization enables effective direct data-driven LQR control for ill-conditioned data, shown equivalent to indirect Tikhonov-regularized LQR and extended to nonlinear systems via Koopman embedding.
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Data-Driven Co-Design of Event-Triggered and Sparse Control for Resource-Aware Networked Control Systems
A unified data-driven co-design method for event-triggered and sparse control in noisy NCS with unknown dynamics, providing stability and H_infty conditions via iterative optimization.
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On Tikhonov Regularization for Direct and Indirect Data-Driven LQR Control
A new regularized covariance parameterization enables effective direct data-driven LQR control for ill-conditioned data, shown equivalent to indirect Tikhonov-regularized LQR and extended to nonlinear systems via Koopman embedding.