Carlos Canudas de Wit – Scales Paradigms in Control & Estimation of Large-scale networks | LIG – Laboratoire d’Informatique de Grenoble
- Keynote Speech
Place and time : Amphithéâtre du bâtiment IMAG at 14:00 on February 6, 2020
Organized by : Team Keynote of LIG : Frédéric Prost, Renaud Lachaize, Dominique Vaufreydaz
Speaker : Carlos Canudas de Wit
In this talk we presents some results from the ERC Scale-FreeBAck on the problem of controlling aggregates of large-scale complex systems with a few inputs (micro-control). Aggregates here are “aggregated” variables functions of the systems state-space variables such as mean values (macro-outputs). Examples of such a class of systems are traffic networks, Brain neural networks, heating systems, among others. The basic idea is to devise a “virtual” aggregated model of the original large-scale system using the scale-free (SF) metric, which indicate that the degree distributions of the associated graph follows an exponential decaying law.Then, we discuss different partitioning algorithms leading to aggregated graphs with the SF desired distribution but also with the suited control/observation properties. In the talk, I also present the mathematical properties necessary for the average observability.The second part of the talk, presents a different alternative for cutting system complexity, which consist in representing a large traffic network as a continuum. That is, to approximate a large-scale dynamic graph (where each node represent a variable), by Partial Differential Equations. The objective of this second approach is to use the PDE model for designing boundary estimators and control.