9 papers
Online Feedback Optimization for Monotone Systems without Timescale Separation
Mattia Bianchi, Florian Dörfler
Online Feedback Optimization (OFO) steers a dynamical plant to a cost-efficient steady-state, only relying on input-output sensitivity information, rather than on a full plant mode…
Split-as-a-Pro: behavioral control via operator splitting and alternating projections
Yu Tang, Carlo Cenedese, Alessio Rimoldi +3
The paper introduces Split-as-a-Pro, a control framework that integrates behavioral systems theory, operator splitting methods, and alternating projection algorithms. The framework…
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
Colin Dirren, Mattia Bianchi, Panagiotis D. Grontas +2
We study the convex-concave bilinear saddle-point problem , where both, only one, or none of the functions and are strongly convex, a…
Maximum likelihood inference for high-dimensional problems with multiaffine variable relations
Jean-Sébastien Brouillon, Florian Dörfler, Giancarlo Ferrari-Trecate
Maximum Likelihood Estimation of continuous variable models can be very challenging in high dimensions, due to potentially complex probability distributions. The existence of multi…
Distributed Traffic Signal Control via Coordinated Maximum Pressure-plus-Penalty
Vinzenz Tütsch, Zhiyu He, Florian Dörfler +1
This paper develops an adaptive traffic control policy inspired by Maximum Pressure (MP) while imposing coordination across intersections. The proposed Coordinated Maximum Pressure…
Minimal regret state estimation of time-varying systems
Jean-Sébastien Brouillon, Florian Dörfler, Giancarlo Ferrari-Trecate
Kalman and H-infinity filters, the most popular paradigms for linear state estimation, are designed for very specific specific noise and disturbance patterns, which may not appear…
Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control
Andrea Martin, Luca Furieri, Florian Dörfler +2
We consider control of dynamical systems through the lens of competitive analysis. Most prior work in this area focuses on minimizing regret, that is, the loss relative to an ideal…
An Extended Kalman Filter for Data-enabled Predictive Control
Daniele Alpago, Florian Dorfler, John Lygeros
The literature dealing with data-driven analysis and control problems has significantly grown in the recent years. Most of the recent literature deals with linear time-invariant sy…
Regularized and Distributionally Robust Data-Enabled Predictive Control
Jeremy Coulson, John Lygeros, Florian Dörfler
In this paper, we study a data-enabled predictive control (DeePC) algorithm applied to unknown stochastic linear time-invariant systems. The algorithm uses noise-corrupted input/ou…