activity
20162019
collaborators

5 papers

eess.SY2019

Abstractions of linear dynamic networks for input selection in local module identification

Harm H. M. Weerts, Jonas Linder, Martin Enqvist +1

In abstractions of linear dynamic networks, selected node signals are removed from the network, while keeping the remaining node signals invariant. The topology and link dynamics,…

eess.SY2018

Single module identifiability in linear dynamic networks

Harm Weerts, Paul M. J. Van den Hof, Arne Dankers

A recent development in data-driven modelling addresses the problem of identifying dynamic models of interconnected systems, represented as linear dynamic networks. For these netwo…

eess.SY2017

Prediction error identification of linear dynamic networks with rank-reduced noise

Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers

Dynamic networks are interconnected dynamic systems with measured node signals and dynamic modules reflecting the links between the nodes. We address the problem of \red{identifyin…

eess.SY2017

Identification in Dynamic Networks

Paul M. J. Van den Hof, Arne G. Dankers, Harm H. M. Weerts

System identification is a common tool for estimating (linear) plant models as a basis for model-based predictive control and optimization. The current challenges in process indust…

eess.SY2016

Identifiability of linear dynamic networks

Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers

Dynamic networks are structured interconnections of dynamical systems (modules) driven by external excitation and disturbance signals. In order to identify their dynamical properti…