5 citations · 17 across the 15 of their papers we have counts for
19 papers
Steering dynamic network centrality via control theory
Fabio Durastante, Beatrice Meini, Luca Saluzzi
Time-evolving networks, or temporal networks, play a crucial role in modeling dynamic interactions across various domains, including biology, social sciences, and information techn…
High order Tensor-Train-Based Schemes for High-Dimensional Mean Field Games
Elisabetta Carlini, Luca Saluzzi
We introduce a fully discrete scheme to solve a class of high-dimensional Mean Field Games systems. Our approach couples semi-Lagrangian (SL) time discretizations with Tensor-Train…
The State-Dependent Riccati Equation in Nonlinear Optimal Control: Analysis, Error Estimation and Numerical Approximation
Luca Saluzzi
The State-Dependent Riccati Equation (SDRE) approach is extensively utilized in nonlinear optimal control as a reliable framework for designing robust feedback control strategies.…
Separable Approximations of Optimal Value Functions and Their Representation by Neural Networks
Mario Sperl, Luca Saluzzi, Dante Kalise +1
The use of separable approximations is proposed to mitigate the curse of dimensionality related to the approximation of high-dimensional value functions in optimal control. The sep…
Dynamical Low-Rank Approximation Strategies for Nonlinear Feedback Control Problems
Luca Saluzzi, Maria Strazzullo
This paper addresses the stabilization of dynamical systems in the infinite horizon optimal control setting using nonlinear feedback control based on State-Dependent Riccati Equati…
On the data-sparsity of the solution of Riccati equations with applications to feedback control
Stefano Massei, Luca Saluzzi
Solving large-scale continuous-time algebraic Riccati equations is a significant challenge in various control theory applications. This work demonstrates that when the matrix coeff…