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
This paper discusses robustness guarantees for online tracking of time-varying subspaces from noisy data. Building on recent work in optimization over a Grassmannian manifold, we i…
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…
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…
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,…