Finding Conditions for Target Controllability under Christmas Trees
Marco Peruzzo, Giacomo Baggio, Francesco Ticozzi
TL;DR
This work addresses identifying target-controllable node sets in directed networks from a structural standpoint. It introduces Christmas trees, a blended topology combining cycles and tree-like branches, and develops a graph-theoretic target-controllability condition for elementary Christmas trees by revealing a block-diagonal structure of the output controllability matrix, denoted by $\hat{\mathcal{R}}_k$, across periodic classes with diagonal weights $D^{(i)}$. The approach yields a sufficient criterion that extends beyond existing criteria (such as the $k$-walk and stem-cycle conditions) and can identify target-controllable sets not detectable by prior results, while remaining applicable to general networks through spanning subgraphs of the Christmas-tree class. The findings illuminate how simple, expressive topologies can capture nontrivial controllability properties and point toward a more complete characterization of structural target controllability in broader network classes, with future work aiming to achieve necessity and extend to full Christmas trees.
Abstract
This paper presents new graph-theoretic conditions for structural target controllability of directed networks. After reviewing existing conditions and highlighting some gaps in the literature, we introduce a new class of network systems, named Christmas trees, which generalizes trees and cacti. We then establish a graph-theoretic characterization of sets of nodes that are structurally target controllable for a simple subclass of Christmas trees. Our characterization applies to general network systems by considering spanning subgraphs of Christmas tree class and allows us to uncover target controllable sets that existing criteria fail to identify.
