Structural approaches to dynamical networks: from nature to engineering (and back)

July 23, 2019
Versione stampabile

Venue: Room A213, Polo F.Ferrari 1 – via Sommarive 9 - Trento 


  • Giulia Giordano, Delft University of Technology, The Netherlands

Many engineering systems (such as sensor networks, telecommunication and transportation systems, multi-agent robotics) and natural phenomena (such as biological and biochemical systems, food webs and social networks) can be modelled as dynamical networks. A dynamical network is composed of several dynamic subsystems that interact according to a precise interconnection topology, i.e. the system "structure".Structural approaches exploit the knowledge of the system structure to efficiently control the global system behaviour through suitably designed local interactions, and to assess qualitative system properties that hold regardless of parameter values.

First, we illustrate network-decentralised control strategies where several local controllers - each associated with an arc of the interconnection graph - can be designed, under suitable conditions, to guarantee stability of the global dynamics whenever the overall system is stabilisable. We discuss the asymptotic optimality properties of network-decentralised controllers, and we briefly introduce the dual concept of network-decentralised estimation.

Then we consider structural analysis and, focusing on biological systems, we discuss structural criteria for stability, for signed steady-state input-output influences, and for a classification of oscillatory and multistationary transitions to instability in sign-definite systems. Our investigation of parameter-free properties relies on the "BDC-decomposition", introduced to capture the system structure. Identifying structural properties enables us not only to better understand natural phenomena, but also to synthesise artificial biomolecular systems with the desired functionality.

Looking at the structure can help us learn from nature in engineering and engineer nature, in order to build engineered systems that are structured to be as robust and resilient as natural systems, and to devise novel biomolecular circuits that are structurally guaranteed to behave as desired.


Giulia Giordano received the B.Sc. and M.Sc. degrees summa cum laude in electrical engineering and the Ph.D. degree in systems and control theory from the University of Udine, Italy, in 2010, 2012, and 2016, respectively. Since 2017 she has been an Assistant Professor at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. She visited the Control and Dynamical Systems group, California Institute of Technology, Pasadena, CA, USA, in 2012 and the Institute of Systems Theory and Automatic Control at the University of Stuttgart, Germany, in 2015. Between 2016 and 2017 she was with the Department of Automatic Control and LCCC Linnaeus Center, Lund University, Sweden.

Her main research interests include the study of dynamical networks, the analysis of biological systems and the control of networked systems.

She received the EECI PhD Award 2016 for her thesis "Structural Analysis and Control of Dynamical Networks" and the NAHS Best Paper Award 2017 as a coauthor of the paper "A Switched System Approach to Dynamic Race Modelling," Nonlinear Analysis: Hybrid Systems, 2016. In 2018 she was awarded a Delft Technology Fellowship.