27 citations · 104 across the 22 of their papers we have counts for
29 papers
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…
Harnessing Uncertainty for a Separation Principle in Direct Data-Driven Predictive Control
Alessandro Chiuso, Marco Fabris, Valentina Breschi +1
Model Predictive Control (MPC) is a powerful method for complex system regulation, but its reliance on an accurate model poses many limitations in real-world applications. Data-dri…
Dynamic Brain Networks with Prescribed Functional Connectivity
Umberto Casti, Giacomo Baggio, Danilo Benozzo +3
In this paper, we consider stable stochastic linear systems modeling whole-brain resting-state dynamics. We parametrize the state matrix of the system (effective connectivity) in t…
Simulation of Nonlinear Systems Trajectories: between Models and Behaviors
Antonio Fazzi, Alessandro Chiuso
In this paper, we study connections between the classical model-based approach to nonlinear system theory, where systems are represented by equations, and the nonlinear behavioral…
On the impact of regularization in data-driven predictive control
Valentina Breschi, Alessandro Chiuso, Marco Fabris +1
Model predictive control (MPC) is a control strategy widely used in industrial applications. However, its implementation typically requires a mathematical model of the system being…
Uncertainty-aware data-driven predictive control in a stochastic setting
Valentina Breschi, Marco Fabris, Simone Formentin +1
Data-Driven Predictive Control (DDPC) has been recently proposed as an effective alternative to traditional Model Predictive Control (MPC), in that the same constrained optimizatio…