Dr. Maestre will give a talk on Data Based Distributed Model Predictive Control at the IFAC Workshop on Game Theory and Learning for Cyber-Physical Systems, organized by Tansu Alpcan, Tamer Basar, Quanyan Zhu, and himself.
Also, he is one of the organizers of the Open Invited Track on Predictive Control of Large-Scale Water Systems, which was proposed in cooperation with Eric Duviella, Laurent Lefevre, and Carlos Ocampo-Martinez.
Finally, the following papers were accepted at the conference and will be presented by members of our team:
- Eva Masero Rubio, J. M. Maestre, Mario Francisco, Eduardo F. Camacho
Coalitional MPC with predicted topology transitions
- Francisco López Rodríguez, J. M. Maestre, Francisco Javier Muros, Eduardo F. Camacho
A Modular Feedback Approach for Distributed Control
- Francisco Javier Muros, J. M. Maestre
An LMI-Based Approach for Semivalues Constraints in Coalitional Feedback Control
- Paula Chanfreut, J. M. Maestre, Quanyan Zhu, Eduardo F. Camacho
No-Regret Learning for Coalitional Model Predictive Control
- Daniel Saracho, Francisco Javier Muros, J. M. Maestre
Efficient Design of Fault Detection Architectures for Power Networks by Using Game Theory
- Paul Trodden, J. M. Maestre, Hideaki Ishii
Actuation attacks on constrained linear systems: a set-theoretic analysis
- Hadger Gedachi, Paula Chanfreut, J. M. Maestre
A nonlinear distributed model predictive scheme for systems based on Hammerstein model
- Paula Chanfreut, Twan Keijzer, Riccardo M.G. Ferrari, J. M. Maestre
A Topology-Switching Coalitional Control and Observation Scheme with Stability Guarantees
- Carmen Amo Alonso, Dimitar Ho, J. M. Maestre
Distributed Linear Quadratic Regulator Robust toCommunication Dropouts
Stay tuned at the official website!