16:00 - 17:00
Title: Clustering-based model reduction of network systems containing cycle
Abstract: In the model reduction of networked systems, clustering-based methods are able to preserve the network structure and synchronisation properties. However, the selection of clustering that results in a reduced-order model with optimal approximation error remains an open problem. The method of  enables identifying two nodes/sub-systems that show similar behaviour and, therefore, choosing two nodes to be clustered and resulting in a good approximation, based on the analysis of the Gramians of the edge dynamics. This method works perfectly on networked systems with tree structures, but the extension to more general graph structures containing cycles is not straightforward. In this colloquium, I will present my ongoing research on solving the problem of finding the best-clustering of networks containing cycles using the concept of Gramians for semi-stable systems .
 Besselink, Bart, Henrik Sandberg, and Karl H. Johansson. "Clustering-based model reduction of networked passive systems." IEEE Transactions on Automatic Control 61.10 (2015): 2958-2973.
 Cheng, Xiaodong, and Jacquelien MA Scherpen. "Novel Gramians for linear semistable systems." Automatica 115 (2020): 108911.