6 papers
Modeling inhomogeneous spatial point configurations with applications to replicated patterns in waiting crowds
Lars Sickert Karam, Rui M. Castro, Maarten Schoukens +1
In this article, we connect statistical inference for spatial point processes with the analysis of waiting pedestrian crowds through two interconnected contributions. First, on the…
Efficient stochastic model-predictive control based on the meta-state-space representation
Bendegúz Györök, Roland Tóth, Maarten Schoukens +1
Stochastic model-predictive control (SMPC) has evolved to a powerful framework for the control of stochastic dynamical systems. SMPC utilizes a probabilistic uncertainty descriptio…
Data-driven augmentation of first-principles models under constraint-free well-posedness and stability guarantees
Bendegúz Györök, Roel Drenth, Chris Verhoek +3
The integration of first-principles models with learning-based components, i.e., model augmentation, has gained increasing attention, as it offers higher model accuracy and faster…
A frequency-domain approach for estimating continuous-time diffusively coupled linear networks
Desen Liang, E. M. M., Kivits +2
This paper addresses the problem of consistently estimating a continuous-time (CT) diffusively coupled network (DCN) to identify physical components in a physical network. We devel…
Measurements and System Identification for the Characterization of Smooth Muscle Cell Dynamics
Dilan Ozturk, Pepijn Saraber, Kevin Bielawski +4
Biological tissue integrity is actively maintained by cells. It is essential to comprehend how cells accomplish this in order to stage tissue diseases. However, addressing the comp…
Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees
Thomas de Jong, Valentina Breschi, Maarten Schoukens +1
In this paper, we consider the design of data-driven predictive controllers for nonlinear systems from input-output data via linear-in-control input Koopman lifted models. Instead…