3 citations · 6 across the 4 of their papers we have counts for
8 papers
State-dependent Riccati equation feedback stabilization for nonlinear PDEs
Alessandro Alla, Dante Kalise, Valeria Simoncini
The synthesis of suboptimal feedback laws for controlling nonlinear dynamics arising from semi-discretized PDEs is studied. An approach based on the State-dependent Riccati Equatio…
Gradient-augmented Supervised Learning of Optimal Feedback Laws Using State-dependent Riccati Equations
Giacomo Albi, Sara Bicego, Dante Kalise
A supervised learning approach for the solution of large-scale nonlinear stabilization problems is presented. A stabilizing feedback law is trained from a dataset generated from St…
Moment-Driven Predictive Control of Mean-Field Collective Dynamics
G. Albi, M. Herty, D. Kalise +1
The synthesis of control laws for interacting agent-based dynamics and their mean-field limit is studied. A linearization-based approach is used for the computation of sub-optimal…
Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression
Behzad Azmi, Dante Kalise, Karl Kunisch
A sparse regression approach for the computation of high-dimensional optimal feedback laws arising in deterministic nonlinear control is proposed. The approach exploits the control…
Shape Optimization of Actuators over Banach Spaces for Nonlinear Systems
M. Sajjad Edalatzadeh, Dante Kalise, Kirsten A. Morris +1
In this paper, optimal actuator shape for nonlinear parabolic systems is discussed. The system under study is an abstract differential equation with a locally Lipschitz nonlinear p…
Tensor Decomposition Methods for High-dimensional Hamilton-Jacobi-Bellman Equations
Sergey Dolgov, Dante Kalise, Karl Kunisch
A tensor decomposition approach for the solution of high-dimensional, fully nonlinear Hamilton-Jacobi-Bellman equations arising in optimal feedback control of nonlinear dynamics is…