2 citations · 5 across the 11 of their papers we have counts for
11 papers
Gaussian behaviors and stochastic data-driven control
András Sasfi, Alberto Padoan, Ivan Markovsky +1
We propose a stochastic behavioral modeling framework, termed Gaussian behaviors, which augments a deterministic linear time-invariant (LTI) behavior with a Gaussian noise componen…
Stability, Contraction, and Controllers for Affine Systems
L. P. Wieringa, A. Padoan, F. Dorfler +1
Recent developments in data-driven control have revived interest in the behavioral approach to systems theory, where systems are defined as sets of trajectories rather than being d…
Min-Max Grassmannian Optimization for Online Subspace Tracking
Shreyas Bharadwaj, Bamdev Mishra, Cyrus Mostajeran +3
We propose GeRoST (Geometrically Robust Subspace Tracking), an online subspace tracking algorithm that models uncertainty in a subspace using a Grassmannian ball. We derive an exac…
Data-driven generalized perimeter control: Zürich case study
Alessio Rimoldi, Carlo Cenedese, Alberto Padoan +2
Urban traffic congestion is a key challenge for the development of modern cities, requiring advanced control techniques to optimize existing infrastructures usage. Despite the exte…
From Time Series to Affine Systems
A. Padoan, J. Eising, I. Markovsky
The paper extends core results of behavioral systems theory from linear to affine time-invariant systems. We characterize the behavior of affine time-invariant systems via kernel,…
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…
Gaussian behaviors: representations and data-driven control
András Sasfi, Ivan Markovsky, Alberto Padoan +1
We propose a modeling framework for stochastic systems, termed Gaussian behaviors, that describes finite-length trajectories of a system as a Gaussian process. The proposed model n…
Mixed Small Gain and Phase Theorem: A new view using Scale Relative Graphs
Eder Baron-Prada, Adolfo Anta, Alberto Padoan +1
We introduce a novel approach to feedback stability analysis for linear time-invariant (LTI) systems, overcoming the limitations of the sectoriality assumption in the small phase t…
Stability results for MIMO LTI systems via Scaled Relative Graphs
Eder Baron-Prada, Alberto Padoan, Adolfo Anta +1
This paper proposes a frequency-wise approach for stability analysis of multi-input, multi-output (MIMO) Linear Time-Invariant (LTI) feedback systems through Scaled Relative Graphs…
GREAT: Grassmannian REcursive Algorithm for Tracking & Online System Identification
András Sasfi, Alberto Padoan, Ivan Markovsky +1
This paper introduces an online approach for identifying time-varying subspaces defined by linear dynamical systems. The approach of representing linear systems by non-parametric s…
DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization
Michael Cummins, Alberto Padoan, Keith Moffat +2
This paper introduces Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization (DeePC-Hunt), a backpropagation-based method for automatic hyperparamete…