4 papers
Robust Space-Filling Input Design via Stochastic Optimization
Máté Kiss, Roland Tóth, Maarten Schoukens
The space-filling input design approach generates a so-called space-filling dataset in the feature space of the system model. The design method is applicable on a broad class of mo…
Least Costly Space-Filling Experiment Design for the Identification of a Nonlinear System
Máté Kiss, Maarten Schoukens, Roland Tóth
The quality of an estimated nonlinear model highly depends on the data quality that was used for the system identification. By using a Gaussian Process-based optimal input design a…
On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach
Yuhan Liu, Máté Kiss, Roland Tóth +1
While optimal input design for linear systems has been well-established, no systematic approach exists for nonlinear systems where robustness to extrapolation/interpolation errors…
Space-Filling Input Design for Nonlinear State-Space Identification
Máté Kiss, Roland Tóth, Maarten Schoukens
The quality of a model resulting from (black-box) system identification is highly dependent on the quality of the data that is used during the identification procedure. Designing e…