Reference:
S. Shi,
X. Cheng,
B. De Schutter, and
P.M.J. Van den Hof,
"Signal selection for local module identification in linear dynamic
networks: A graphical approach," Proceedings of the 22nd IFAC
World Congress, Yokohama, Japan, pp. 2407-2412, July 2023.
Abstract:
In a dynamic network of interconnected transfer functions, it is not
necessary to use all the node signals for estimating a local transfer
function. Given the network topology, detailed conditions are
available for selecting inputs and outputs in a (MIMO) predictor model
that warrants consistent and minimum variance estimation of a target
module through the so-called local direct method. Motivated by the
existing minimum-input signal selection approach that gradually
incorporates additional signals, an alternative graphical algorithm
for signal selection is developed in this work by directly exploiting
the complete network graph. Then, as a straightforward application of
existing analytical results, graphical conditions for consistent
identification are derived for the novel signal selection approach. We
show by an example that in some cases, for the consistent estimation
of the target module, the developed method leads to fewer selected
signals than the original minimum-input method.
Bibtex entry:
@inproceedings{ShiChe:23-029,