Seminar Details
2026-09-01 (14:00) : Exploring the Impact of Memory on Network Controllability
At Euler building (room A.207)
Duration: 60 minutes
Organized by Mathematical Engineering
Speaker :
Marco Peruzzo (University of Padova)
Marco Peruzzo
Marco Peruzzo received his B.Sc. in Computer Engineering in 2021 and his M.Sc. in Control Systems Engineering in 2023, both from the University of Padova, Italy. He is currently a Ph.D. student at the Department of Information Engineering, University of Padova. In early 2026, he was a visiting scholar at the School of Mathematical Sciences, University of Nottingham, UK. His research interests include the analysis, control, and identification of networked dynamical systems and quantum systems.
Abstract :
Many natural and engineered dynamical systems can be modeled as networks consisting of a large number of interconnected, simpler dynamical units. Over the last decade, the challenge of efficiently controlling large-scale networks has driven renewed interest in the control community. Several strategies for guaranteeing network controllability have been developed, such as the optimal selection of driver nodes and the implementation of minimal changes to the network topology.
In this talk, we explore a different strategy for achieving controllability, motivated by networks whose topology cannot be easily modified, such as traffic and water-flow networks. Inspired by lifted Markov chains, we enlarge the local state space of selected network nodes, introducing memory and directionality into their dynamics while leaving the network topology unchanged. We show that this strategy can reduce the worst-case control energy by a factor exponential in the network size.
We further discuss how our strategy can render otherwise uncontrollable networks structurally controllable (i.e., controllable for almost all choices of the network parameters). We characterize networks for which different types of dynamics modifications are required and show that our approach can require significantly fewer subsystem modifications than alternative local dynamics modification strategies.