A Boltzmann approach to mean-field sparse feedback control*. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Albi, Giacomo; Fornasier, Massimo; Kalise, Dante
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 2898
• Page End: 2903
• Publication Date: 2017-07
• Subjects: Multi-agent systems -- sparse control -- feedback control -- mean-field models; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.646
• Languages: English
• ISSNs: 2405-8963

Abstract

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.