Excitation allocation for generic identifiability of linear dynamic networks with fixed modules

Excitation allocation for generic identifiability of linear dynamic networks with fixed modules

Dreef, H. J. (Eindhoven University of Technology)
Shi, S. (TU Delft Team Bart De Schutter)
Cheng, X. (University of Cambridge)
Donkers, M. C.F. (Eindhoven University of Technology)
Van den Hof, P. M.J. (Eindhoven University of Technology)

2022

Identifiability of linear dynamic networks requires the presence of a sufficient number of external excitation signals. The problem of allocating a minimal number of external signals for guaranteeing generic network identifiability in the full measurement case has been recently addressed in the literature. Here we will extend that work by explicitly incorporating the situation that some network modules are known, and thus are fixed in the parametrized model set. The graphical approach introduced earlier is extended to this situation, showing that the presence of fixed modules reduces the required number of external signals. An algorithm is presented that allocates the external signals in a systematic fashion.

Dynamic scheduling
Heuristic algorithms
identification
linear systems.
Network analysis and control
Network topology
Numerical models
Resource management
Topology
White noise

http://resolver.tudelft.nl/uuid:143b4c45-0f61-45c8-af7a-cd1d8031694e

https://doi.org/10.1109/LCSYS.2022.3171172

2475-1456

IEEE Control Systems Letters, 6, 2587-2592

Accepted Author Manuscript

Institutional Repository

journal article

© 2022 H. J. Dreef, S. Shi, X. Cheng, M. C.F. Donkers, P. M.J. Van den Hof