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Saverio Bolognani

Dr.
Saverio Bolognani
Principal Investigators
Management
ETH Zurich
bsaverio@ethz.ch
Curriculum Vitae
Feedback is the principle behind efficient interaction as well as cascading failures. We need to understand feedback to understand autonomous systems.

Saverio Bolognani received the Ph.D. degree in Information Engineering from the University of Padova, Italy, in 2011. In 2013 – 2014 he was a Postdoctoral Associate at the Laboratory for Information and Decision Systems of the Massachusetts Institute of Technology in Cambridge (MA). He is currently a Senior Researcher at the Automatic Control Laboratory at ETH Zurich. His research interests include the application of control system theory to power systems, distributed control, online optimization, cyber-physical systems, and game theory for multi-agent autonomous systems.

Wissenschaftliche Publikationen

Published
Adaptive real-time grid operation via Online Feedback Optimization with sensitivity estimation
Electric Power Systems Research
Vol 212 Pages 108405
Miguel Picallo, Lukas Ortmann, Saverio Bolognani, Florian Dörfler
Doi.org
Published
How Bad is Selfish Driving? Bounding the Inefficiency of Equilibria in Urban Driving Games
IEEE Robotics and Automation Letters
Vol 8 No 4 Pages 2293
Alessandro Zanardi, Pier Giuseppe Sessa, Nando Käslin, Saverio Bolognani, Andrea Censi, Emilio Frazzoli
Doi.org
Published
Deployment of an Online Feedback Optimization Controller for Reactive Power Flow Optimization in a Distribution Grid
ArXiv
Lukas Ortmann, Christian Rubin, Alessandro Scozzafava, Janick Lehmann, Saverio Bolognani, Florian Dörfler
Collection Arxiv.org
Published
Virtual Power Grid Reinforcement via Coordinated Volt/VAr Control
ArXiv
Jonas G. Matt, Lukas Ortmann, Saverio Bolognani, Florian Dörfler
Collection Arxiv.org
Published
A Self-Contained Karma Economy for the Dynamic Allocation of Common Resources
Dynamic Games and Applications
Ezzat Elokda, Saverio Bolognani, Andrea Censi, Florian Dörfler, Emilio Frazzoli
Collection
Published
Factorization of Dynamic Games over Spatio-Temporal Resources
35th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
Pages 13159 - 13166
Alessandro Zanardi, Saverio Bolognani, Andrea Censi, Florian Dörfler, Emilio Frazzoli
Doi.org
Published
Real-time Curative Actions for Power Systems via Online Feedback Optimization
ArXiv
Lukas Ortmann, Gianni Hotz, Saverio Bolognani, Florian Dörfler
Doi.org Collection
Published
Real-Time Feasibility of Data-Driven Predictive Control for Synchronous Motor Drives
IEEE Transactions on Power Electronics
Vol 38 No 2 Pages 1672
Paolo Gherardo Carlet, Andrea Favato, Riccardo Torchio, Francesco Toso, Saverio Bolognani, Florian Dörfler
Doi.org
Published
A Dynamic Population Model of Strategic Interaction and Migration under Epidemic Risk
2021 60th IEEE Conference on Decision and Control (CDC)
Pages 2085-2091
Ezzat Elokda, Saverio Bolognani, Ashish Hota
Doi.org Collection
Published
Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression
Journal of Process Control
Vol 121 No 119
Marta Zagorowska, M. Degner, Lukas Ortmann, A. Ahmed, Saverio Bolognani, E. A. del Rio Chanona, M. Mercangoz
Doi.org Collection
Published
Posetal Games: Efficiency, Existence, and Refinement of Equilibria in Games With Prioritized Metrics
IEEE Robotics and Automation Letters
Vol 7 No 2 Pages 1292-1299
Alessandro Zanardi, Gioele Zardini, Sirish Srinivasan, Saverio Bolognani, Andrea Censi, Florian Dörfler, Emilio Frazzoli
Doi.org Collection
Published
Cross-layer design for real-time grid operation: Estimation, optimization and power flow
Electric Power Systems Research
Vol 212 No 108378
Miguel Picallo, Dominic Liao-McPherson, Saverio Bolognani, Florian Dörfler
Collection
Published
Sensitivity Conditioning: Beyond Singular Perturbation for Control Design on Multiple Time Scales
IEEE Transactions on Automatic Control
Vol 68 No 4 Pages 2309
Miguel Picallo, Saverio Bolognani, Florian Dörfler
Doi.org
Urban Driving Games With Lexicographic Preferences and Socially Efficient Nash Equilibria
IEEE Robotics and Automation Letters
Vol 6 No 3 Pages 4978 – 4985
Alessandro Zanardi, Enrico Mion, Mattia Bruschetta, Saverio Bolognani, Andrea Censi, Emilio Frazzoli
Collection
Sampled-Data Online Feedback Equilibrium Seeking: Stability and Tracking
60th IEEE Conference on Decision and Control (CDC21)
Dominic Liao-McPherson, Mathias Badyn, Saverio Bolognani, John Lygeros, Florian Dörfler
Collection
Game Theoretical Motion Planning - Tutorial session
IEEE International Conference on Robotics and Automation (ICRA)
Andrea Censi, Saverio Bolognani, Alessandro Zanardi, Emilio Frazzoli
Collection

Forschungsprojekte als Forscher/-in

Titel
Leitende Forscher/-innen

Online Feedback Optimization with Self-Interested Agents for Energy Management Applications

Florian Dörfler

Zusammenfassung

Online feedback optimization refers to the design of feedback controllers that asymptotically steer a physical system to the solution of an optimization problem while respecting physical and operational constraints. Here we are interested in exploring self-interested agents that do not want to cooperate for the sake of achieving a common goal but first and foremost have their own interest in mind. A relevant real-world example is selfish and uncoordinated congestion control by different power transmission system operators. We will investigate distributed Nash-seeking algorithms to solve the resulting antagonistic decision-making problems, and also deploy them in numerical and real-world case studies.

People involved

Florian Dörfler
Florian Dörfler, Saverio Bolognani
Online Feedback Optimization with Self-Interested Agents for Energy Management Applications
Florian Dörfler

Online feedback optimization refers to the design of feedback controllers that asymptotically steer a physical system to the solution of an optimization problem while respecting physical and operational constraints. Here we are interested in exploring self-interested agents that do not want to cooperate for the sake of achieving a common goal but first and foremost have their own interest in mind. A relevant real-world example is selfish and uncoordinated congestion control by different power transmission system operators. We will investigate distributed Nash-seeking algorithms to solve the resulting antagonistic decision-making problems, and also deploy them in numerical and real-world case studies.

Florian Dörfler
Florian Dörfler, Saverio Bolognani
102
7b2b32e9-400f-4978-84c3-7e7316f1c773

Optimization Flows on Probability Distribution Spaces

Florian Dörfler

Zusammenfassung

We want to develop continuous-time optimality-seeking algorithms on the space of probability distributions. We envision our approach to result in practically useful algorithms to probabilistic (e.g. distributionally robust) optimization problems. Furthermore, our framework is directly applicable to optimization and control of traffic flow in a density modelling approach or a continuum modelling of multi-agent systems.

People involved

Florian Dörfler
Florian Dörfler, Saverio Bolognani
Optimization Flows on Probability Distribution Spaces
Florian Dörfler

We want to develop continuous-time optimality-seeking algorithms on the space of probability distributions. We envision our approach to result in practically useful algorithms to probabilistic (e.g. distributionally robust) optimization problems. Furthermore, our framework is directly applicable to optimization and control of traffic flow in a density modelling approach or a continuum modelling of multi-agent systems.

Florian Dörfler
Florian Dörfler, Saverio Bolognani
101
bcd7d27a-de53-49f7-949b-9a48b4ec7eb6

Dynamic population games for efficient autonomous mobility

Florian Dörfler, Emilio Frazzoli

Zusammenfassung

We will demonstrate that multiple competitive agents can efficiently share a mobility infrastructure without the need for an external coordinator. Standard game-theoretic approaches to this problem fall short in case of dynamic systems as encountered in autonomous mobility, coordinated use of the mobility space, traffic congestion control, etc.  We will develop a new mathematical formalism and computational methods blending the concept of game-theoretic and dynamic equilibria. Autonomous mobility is an important application due to the importance of fairness and efficiency in resource use, the large number of interacting agents, and the need for automated and scalable solutions.

People involved

Florian Dörfler
Emilio Frazzoli
Ezzat Elokda
Florian Dörfler, Emilio Frazzoli, Ezzat Elokda, , Saverio Bolognani, , Andrea Censi
Dynamic population games for efficient autonomous mobility
Florian Dörfler, Emilio Frazzoli

We will demonstrate that multiple competitive agents can efficiently share a mobility infrastructure without the need for an external coordinator. Standard game-theoretic approaches to this problem fall short in case of dynamic systems as encountered in autonomous mobility, coordinated use of the mobility space, traffic congestion control, etc.  We will develop a new mathematical formalism and computational methods blending the concept of game-theoretic and dynamic equilibria. Autonomous mobility is an important application due to the importance of fairness and efficiency in resource use, the large number of interacting agents, and the need for automated and scalable solutions.

Florian Dörfler
Emilio Frazzoli
Ezzat Elokda
Florian Dörfler, Emilio Frazzoli, Ezzat Elokda, , Saverio Bolognani, , Andrea Censi
100
25d61593-91d6-4a68-b2c0-4b5078f9de13

Besuchte Veranstaltungen

News & Hintergründe

Photo: Bundesamt für Energie
25. April 2024
Team des NFS Automation gewinnt Watt d'Or für effiziente und nachhaltige Stromversorgung mit Fotovoltaik
sustainable automation
Forschende des NFS Automation vom Laboratorium für Regelungstechnik der ETH Zürich und des Stromversorgers AEW Energie AG haben den Watt d'Or 2024 in der Kategorie Energietechnologien gewonnen. Ihr Algorithmus, der bei AEW Energie implementiert wurde, ermöglicht es, den Betrieb von Stromnetzen zu optimieren.
Schematic of power grid optimization
24. April 2023
Smart-Grid-Lösung für die Schweizer Energiezukunft
In einer Zeit, in der Länder auf der ganzen Welt von Energieknappheit bedroht sind, haben ETH Zürich / NFS Automation -Forscher eine wirkungsvolle und kostengünstige Softwarelösung entwickelt, um die Nutzung dezentraler Energieressourcen zu verbessern. Dieser innovative Ansatz ermöglicht es Netzbetreibern, beispielsweise Photovoltaikanlagen durch einen flexiblen, reaktionsschnellen und datengesteuerten Betrieb optimal zu nutzen.