6 papers
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.…
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…
Hook-Based Aerial Payload Grasping from a Moving Platform
Péter Antal, Tamás Péni, Roland Tóth
This paper investigates payload grasping from a moving platform using a hook-equipped aerial manipulator. First, a computationally efficient trajectory optimization based on comple…
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…
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…
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…