899 citations · 4k across the 136 of their papers we have counts for
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Bounded Linear Programs for Data-Driven Optimal Control via Moment-Matching
Andrea Martinelli, Lucia Pezzetti, Niklas Schmid +2
Linear programming (LP) formulations offer a conceptually elegant approach to infinite-horizon, model-free nonlinear optimal control in continuous spaces. However, in addition to t…
Adaptive Linear Quadratic Control of Unknown Linear Time-Varying Systems via Policy Gradient Methods
Feiran Zhao, Florian Dörfler
Unknown linear time-varying (LTV) systems require the control policy to adapt from online closed-loop data as dynamics evolve. Existing methods usually update the policy by solving…
Distributionally Robust Linear Quadratic Gaussian Regulator with Stationary Distributions
Alain Schöbi, Nicolas Lanzetti, Florian Dörfler +2
We study the Linear Quadratic Gaussian regulation problem in the face of worst-case noise distributions when these are mutually independent, zero-mean, stationary, and within a rad…
Gray-Box Nonlinear Feedback Optimization
Zhiyu He, Saverio Bolognani, Michael Muehlebach +1
Feedback optimization enables autonomous optimality seeking of a dynamical system through its closed-loop interconnection with iterative optimization algorithms. Among various iter…
Online Feedback Optimization over Networks: A Distributed Model-free Approach
Wenbin Wang, Zhiyu He, Giuseppe Belgioioso +2
Online feedback optimization (OFO) enables optimal steady-state operations of a physical system by employing an iterative optimization algorithm as a dynamic feedback controller. W…
Optimal control of continuous-time symmetric systems with unknown dynamics and noisy measurements
Hamed Taghavian, Florian Dorfler, Mikael Johansson
An iterative learning algorithm is presented for continuous-time linear-quadratic optimal control problems where the system is externally symmetric with unknown dynamics. Both fini…
Data-Enabled Policy Optimization for Direct Adaptive Learning of the LQR
Feiran Zhao, Florian Dörfler, Alessandro Chiuso +1
Direct data-driven design methods for the linear quadratic regulator (LQR) mainly use offline or episodic data batches, and their online adaptation has been acknowledged as an open…
Towards a Systems Theory of Algorithms
Florian Dörfler, Zhiyu He, Giuseppe Belgioioso +3
Traditionally, numerical algorithms are seen as isolated pieces of code confined to an {\em in silico} existence. However, this perspective is not appropriate for many modern compu…
Distributionally Robust Infinite-horizon Control: from a pool of samples to the design of dependable controllers
Jean-Sébastien Brouillon, Andrea Martin, John Lygeros +2
We study control of constrained linear systems with only partial statistical information about the uncertainty affecting the system dynamics and the sensor measurements. Specifical…
Tutorial on Congestion Control in Multi-Area Transmission Grids via Online Feedback Equilibrium Seeking
Giuseppe Belgioioso, Saverio Bolognani, Giulia Pejrani +1
Online feedback optimization (OFO) is an emerging control methodology for real-time optimal steady-state control of complex dynamical systems. This tutorial focuses on the applicat…
Data-driven representations of conical, convex, and affine behaviors
Alberto Padoan, Florian Dörfler, John Lygeros
The paper studies conical, convex, and affine models in the framework of behavioral systems theory. We investigate basic properties of such behaviors and address the problem of con…
Controller implementability: a data-driven approach
Alberto Padoan, Jeremy Coulson, Florian Dörfler
We study the controller implementability problem, which seeks to determine if a controller can make the closed-loop behavior of a given plant match that of a desired reference beha…
Grid-Forming Hybrid Angle Control: Behavior, Stability, Variants and Verification
Ali Tayyebi, Denis Vettoretti, Adolfo Anta +1
This work explores the stability, behavior, variants, and a controller-hardware-in-the-loop (C-HiL) verification of the recently proposed grid-forming (GFM) hybrid angle control (H…
SOS Construction of Compatible Control Lyapunov and Barrier Functions
Michael Schneeberger, Florian Dörfler, Silvia Mastellone
We propose a novel approach to certify closed-loop stability and safety of a constrained polynomial system based on the combination of Control Lyapunov Functions (CLFs) and Control…
Wasserstein Tube MPC with Exact Uncertainty Propagation
Liviu Aolaritei, Marta Fochesato, John Lygeros +1
We study model predictive control (MPC) problems for stochastic LTI systems, where the noise distribution is unknown, compactly supported, and only observable through a limited num…
Designing Optimal Personalized Incentive for Traffic Routing using BIG Hype algorithm
Panagiotis D. Grontas, Carlo Cenedese, Marta Fochesato +3
We study the problem of optimally routing plug-in electric and conventional fuel vehicles on a city level. In our model, commuters selfishly aim to minimize a local cost that combi…
Capture, Propagate, and Control Distributional Uncertainty
Liviu Aolaritei, Nicolas Lanzetti, Florian Dörfler
We study stochastic dynamical systems in settings where only partial statistical information about the noise is available, e.g., in the form of a limited number of noise realizatio…
Data-enabled Policy Optimization for the Linear Quadratic Regulator
Feiran Zhao, Florian Dörfler, Keyou You
Policy optimization (PO), an essential approach of reinforcement learning for a broad range of system classes, requires significantly more system data than indirect (identification…
Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
Soroosh Shafiee, Liviu Aolaritei, Florian Dörfler +1
We study optimal transport-based distributionally robust optimization problems where a fictitious adversary, often envisioned as nature, can choose the distribution of the uncertai…
BIG Hype: Best Intervention in Games via Distributed Hypergradient Descent
Panagiotis D. Grontas, Giuseppe Belgioioso, Carlo Cenedese +3
Hierarchical decision making problems, such as bilevel programs and Stackelberg games, are attracting increasing interest in both the engineering and machine learning communities.…
Dynamic Programming in Probability Spaces via Optimal Transport
Antonio Terpin, Nicolas Lanzetti, Florian Dörfler
We study discrete-time finite-horizon optimal control problems in probability spaces, whereby the state of the system is a probability measure. We show that, in many instances, the…
Online Feedback Equilibrium Seeking
Giuseppe Belgioioso, Dominic Liao-McPherson, Mathias Hudoba de Badyn +4
This paper proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of…
First-order Conditions for Optimization in the Wasserstein Space
Nicolas Lanzetti, Saverio Bolognani, Florian Dörfler
We study first-order optimality conditions for constrained optimization in the Wasserstein space, whereby one seeks to minimize a real-valued function over the space of probability…
A quantitative and constructive proof of Willems' Fundamental Lemma and its implications
Julian Berberich, Andrea Iannelli, Alberto Padoan +3
Willems' Fundamental Lemma provides a powerful data-driven parametrization of all trajectories of a controllable linear time-invariant system based on one trajectory with persisten…