Publications (12)
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…
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…
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models
Stefan Meisenbacher, Benedikt Heidrich, Tim Martin +2
Accurate PhotoVoltaic (PV) power generation forecasting is vital for the efficient operation of Smart Grids. The automated design of such accurate forecasting models for individual…
Accelerating LHC event generation with simplified pilot runs and fast PDFs
Enrico Bothmann, Andy Buckley, Ilektra A. Christidi +5
Poor computing efficiency of precision event generators for LHC physics has become a bottleneck for Monte-Carlo event simulation campaigns. We provide solutions to this problem by…
Control-Oriented System Identification: Classical, Learning, and Physics-Informed Approaches
S. Sivaranjani, Yuanyuan Shi, Nikolay Atanasov +6
The paper surveys classical, machine‑learning, and physics‑informed system identification methods that incorporate control‑relevant properties such as dissipativity and symmetry, d…
Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey
Tim Martin, Thomas B. Schön, Frank Allgöwer
This survey presents recent research on determining control-theoretic properties and designing controllers with rigorous guarantees using semidefinite programming and for nonlinear…