5 papers
Automated Linear Parameter-Varying Modeling of Nonlinear Systems: A Global Embedding Approach
E. Javier Olucha, Patrick J. W. Koelewijn, Amritam Das +1
In this paper, an automated Linear Parameter-Varying (LPV) model conversion approach is proposed for nonlinear dynamical systems. The proposed method achieves global embedding of t…
Gaussian-Process-based Adaptive Tracking Control with Dynamic Active Learning for Autonomous Ground Vehicles
Kristóf Floch, Tamás Péni, Roland Tóth
This article proposes an active-learning-based adaptive trajectory tracking control method for autonomous ground vehicles to compensate for modeling errors and unmodeled dynamics.…
Orthogonal projection-based regularization for efficient model augmentation
Bendegúz M. Györök, Jan H. Hoekstra, Johan Kon +3
Deep-learning-based nonlinear system identification has shown the ability to produce reliable and highly accurate models in practice. However, these black-box models lack physical…
A behavioral approach for LPV data-driven representations
Chris Verhoek, Ivan Markovsky, Sofie Haesaert +1
In this paper, we present a data-driven representation for linear parameter-varying (LPV) systems, which can be used for direct data-driven analysis and control of such systems. Sp…
Scaled Relative Graph Analysis of Lur'e Systems and the Generalized Circle Criterion
Julius P. J. Krebbekx, Roland Tóth, Amritam Das
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from a…