activity
20162024
collaborators

6 papers

eess.SY2024

Data-informativity conditions for structured linear systems with implications for dynamic networks

Paul M. J. Van den Hof, Shengling Shi, Stefanie J. M. Fonken +3

When estimating a single subsystem (module) in a linear dynamic network with a prediction error method, a data-informativity condition needs to be satisfied for arriving at a consi…

eess.SY2018

Local module identification in dynamic networks with correlated noise: the full input case

Paul M. J. Van den Hof, Karthik R. Ramaswamy, Arne G. Dankers +1

The identification of local modules in dynamic networks with known topology has recently been addressed by formulating conditions for arriving at consistent estimates of the module…

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…