A Boltzmann approach to mean-field sparse feedback control

Giacomo Albi, Massimo Fornasier, Dante Kalise

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

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, 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.

Original languageEnglish
Pages (from-to)2898-2903
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume50
Issue number1
DOIs
StatePublished - Jul 2017

Keywords

  • Multi-agent systems
  • feedback control
  • mean-field models
  • sparse control

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