A Boltzmann approach to mean-field sparse feedback control
Optimization and Control
2016-11-15 v1 Mathematical Physics
Dynamical Systems
math.MP
Abstract
We study the synthesis of optimal control policies for large-scale multi-agent systems. The optimal control design induces a parsimonious control intervention by means of l-1, sparsity-promoting control penalizations. We study instantaneous and infinite horizon sparse optimal feedback controllers. In order to circumvent the dimensionality issues associated to the control of large-scale agent-based models, we follow a Boltzmann approach. We generate (sub)optimal controls signals for the kinetic limit of the multi-agent dynamics, by sampling of the optimal solution of the associated two-agent dynamics. Numerical experiments assess the performance of the proposed sparse design.
Cite
@article{arxiv.1611.03988,
title = {A Boltzmann approach to mean-field sparse feedback control},
author = {Giacomo Albi and Massimo Fornasier and Dante Kalise},
journal= {arXiv preprint arXiv:1611.03988},
year = {2016}
}