Francesco Sorrentino
IEEE Circuits and Systems Society joint Chapter of the Vancouver/Victoria Sections
IEEE Control, Robotics, and Cybernetics Joint Chapter of the IEEE Vancouver Section

Prof. Francesco Sorrentino
Department of Mechanical Engineering
University of New Mexico

Title: Dimensionality Reduction of the Pinning Control Problem for Network Synchronization

(Presentation is available in pdf format.)

Friday, September 6, 2024, 4:00 pm to 5:30 pm
ASB 9896, Fraser University, Burnaby, British Columbia, Canada V5A 1S6
Zoom link: https://sfu.zoom.us/j/82782424381?pwd=YHwaQGz1HoZ9K77399zVxBJYyZahmN.1

The event is open to public.
We would greatly appreciate if you would please register.


Abstract

In this talk I review the pinning control problem for synchronization of networks of coupled oscillators. I first consider the case of connections all of the same type. Then I consider the network pinning control problem in the presence of two different types of coupling: (i) node-to-node coupling among the network nodes and (ii) input-to-node coupling from the source node to the `pinned nodes'. For the latter problem, I show how the stability analysis of the target synchronous solution can be decoupled into subproblems of the lowest dimension by using the techniques of simultaneous block diagonalization (SBD) of matrices.

Biography

Francesco Sorrentino is full professor of Automatic Controls in the Department of Mechanical Engineering at the University of New Mexico. He received a master's degree in Industrial Engineering from the University of Naples Federico II (Italy) in 2003 and a Ph.D. in Control Engineering from the University of Naples Federico II (Italy) in 2007.

His expertise is in dynamical systems and controls, with particular emphasis on nonlinear dynamics and optimal control. His work includes studies on dynamics and control of complex dynamical networks, adaptation in complex systems, sensor adaptive networks, and the dynamics of reservoir computers in machine learning. He is interested in applying the theory of dynamical systems to model, analyze, and control the dynamics of complex distributed energy systems, such as power networks and smart grids. Subjects of current investigation are evolutionary game theory on networks (evolutionary graph theory), the dynamics of large networks of coupled neurons, and the use of optimal control to design drug dosage schedules for biomedical applications. He has published more than 80 papers in international scientific peer reviewed journals. He is the awardee of the NIH Trailblazer award.


Last updated 
Wed 11 Sep 2024 21:50:48 PDT.