EconPapers    
Economics at your fingertips  
 

Extremal Shift Rule and Viability Property for Mean Field-Type Control Systems

Yurii Averboukh (), Antonio Marigonda () and Marc Quincampoix ()
Additional contact information
Yurii Averboukh: Krasovskii Institute of Mathematics and Mechanics
Antonio Marigonda: University of Verona
Marc Quincampoix: Univ Brest

Journal of Optimization Theory and Applications, 2021, vol. 189, issue 1, No 11, 244-270

Abstract: Abstract We investigate when a mean field-type control system can fulfill a given constraint. Namely, given a closed set of probability measures on the torus, starting from any initial probability measure belonging to this set, does there exist a solution to the mean field control system remaining in it for any time? This property—the so-called viability property—is equivalently characterized through a property involving normals to the given set of probability measures. We prove that, if the Hamiltonian is nonpositive at any normal distribution to the given set, then the feedback strategy realizing the extremal shift rule provides the approximate viability. This implies the usual viability property. Conversely, the Hamiltonian is nonpositive at any normal distribution if the given set is viable. Our approach enables us to derive generalized feedback laws which ensure the trajectory to fulfill the constraint. This generalized feedback called here extremely shift rule is inspired by constructive motions developed by Krasovskii and Subbotin for differential games.

Keywords: Mean field-type control; Viability; Proximal normal distribution; Extremal shift; 49N35; 93B52; 93C10; 93A14; 28A33 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10957-021-01832-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:189:y:2021:i:1:d:10.1007_s10957-021-01832-z

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-021-01832-z

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:joptap:v:189:y:2021:i:1:d:10.1007_s10957-021-01832-z