Skip to main content


The Dynamic Network Identification Toolbox is developed by a team of researchers and developers under leadership of:

Prof. Paul M.J. Van den Hof
Control Systems Group
Department of Electrical Engineering
Eindhoven University of Technology
Eindhoven, The Netherlands

Project website:

Version: beta-0.3.0
Date: 5 April 2023

Contributions to the algorithms:
    Xiaodong Cheng, Stefanie Fonken, Karthik Ramaswamy, Shengling Shi, Tom Steentjes, Harm Weerts
Contributions to the software implementation:
    Mannes Dreef, Wim Liebregts, Job Meijer, Ilja van Oort, Gareth Thomas (VersionBay)

This project has received funding from the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 694504).

The software is made available under a General Public License GNU 3.0.

Functionality and limitations

The beta-version of the app and toolbox contains a graphical user interface for analyzing structural properties of linear dynamic networks. On the basis of a given network topology, including the location of external excitaton signals and disturbances, tools are provided for the allocation of sensors (where to measure) and external signals (where to excite), for arriving at consistent estimates of either a full network or a single module.

The prime app-windows concern:

  • Loading, viewing and editing a network topology
  • Basic tests and operations on network topologies; node immersion
  • Analyzing and synthesizing module/network identifiability
  • Constructing predictor models (inputs and outputs) for local module identification.

The different technical operations are also available as individual m-files for command window operations.

The maximum network size that can be handled by the current implementation is around 50 nodes.

Future extensions

In the near future the app/toolbox will be extended with data-manipulation and estimation algorithms so as to perform actual identification, and evaluate estimated network models.

Questions and feedback

For any questions, feedback and bug reports, please contact: