EconPapers    
Economics at your fingertips  
 

Subgradients of the Value Function in a Parametric Convex Optimal Control Problem

Le Quang Thuy () and Nguyen Thi Toan ()
Additional contact information
Le Quang Thuy: Hanoi University of Science and Technology
Nguyen Thi Toan: Hanoi University of Science and Technology

Journal of Optimization Theory and Applications, 2016, vol. 170, issue 1, No 3, 43-64

Abstract: Abstract Motivated by our recent works on the optimal value function in parametric optimal control problems under linear state equations, in this paper we study of the first-order behavior of the value function of a parametric convex optimal control problem with a convex cost function and linear state equations. By establishing an abstract result on the subdifferential of the value function to a parametric convex mathematical programming problem, we derive a formula for computing the subdifferential and the singular subdifferential of the value function to a parametric convex optimal control problem. By virtue of the convexity, several assumptions used in the above papers, like the existence of a local upper Lipschitzian selection of the solution map, as well as the V-inner semicontinuity of the solution map, are no longer needed.

Keywords: Parametric convex optimal control problem; Marginal function; Value function; Normal cone; Subdifferential; Singular subdifferential; 49J15; 49J53; 49K15; 90C90 (search for similar items in EconPapers)
Date: 2016
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/s10957-016-0921-2 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:170:y:2016:i:1:d:10.1007_s10957-016-0921-2

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

DOI: 10.1007/s10957-016-0921-2

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:170:y:2016:i:1:d:10.1007_s10957-016-0921-2