DocumentCode
184463
Title
Approximate dynamic programming, local or global optimal solution?
Author
Heydari, Ali ; Balakrishnan, Sivasubramanya N.
Author_Institution
Mech. Eng. Dept., South Dakota Sch. of Mines & Technol., Rapid City, SD, USA
fYear
2014
fDate
4-6 June 2014
Firstpage
1237
Lastpage
1242
Abstract
The problem of global optimality analysis of approximate dynamic programming based solutions is investigated in this study. Sufficient conditions for global optimality is obtained without requiring the state penalizing terms in the cost function or the functions representing the dynamics to be convex functions. Afterwards, the theoretical results are confirmed through a qualitative analysis of an example problem.
Keywords
dynamic programming; optimal control; ADP; approximate dynamic programming; global optimality analysis; optimal control problems; Convex functions; Cost function; Dynamic programming; Equations; Least squares approximations; Optimal control; Learning; Neural networks; Optimal control;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6859117
Filename
6859117
Link To Document