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eess.SY2025
Control-Oriented System Identification: Classical, Learning, and Physics-Informed Approaches
S. Sivaranjani, Yuanyuan Shi, Nikolay Atanasov +6
We survey classical, machine learning, and data-driven system identification approaches to learn control-relevant and physics-informed models of dynamical systems. Recently, machin…
eess.SY2020
Dissipativity verification with guarantees for polynomial systems from noisy input-state data
Tim Martin, Frank Allgöwer
In this paper, we investigate the verification of dissipativity properties for polynomial systems without an explicitly identified model but directly from noise-corrupted measureme…
eess.SY2020
Iterative data-driven inference of nonlinearity measures via successive graph approximation
Tim Martin, Frank Allgöwer
In this paper, we establish an iterative data-driven approach to derive guaranteed bounds on nonlinearity measures of unknown nonlinear systems. In this context, nonlinearity measu…