DocumentCode
319981
Title
Hamiltonian systems, HJB equations, and stochastic controls
Author
Zhou, Xun Yu
Author_Institution
Dept. of Syst. Eng. & Eng. Manage., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Volume
4
fYear
1997
fDate
10-12 Dec 1997
Firstpage
3436
Abstract
Pontraygin´s maximum principle (MP) involving the Hamiltonian system and Bellman´s dynamic programming (DP) involving the HJB equation are the two most important approaches in modern optimal control theory. However, these two approaches have been developed separately in literature and it has been a long-standing, yet fundamentally important problem to disclose the relationship between them and to establish a unified theory. The problem is by no means a “new” one; indeed, it roots in the Hamilton-Jacobi theory in analytic mechanics and method of characteristics in classical PDE theory, and has intrinsic relation with the Feynman-Kac formula in stochastic analysis and shadow price theory in economics. This paper discusses some deep connections between the MP and DP in stochastic optimal controls from various aspects
Keywords
dynamic programming; maximum principle; partial differential equations; stochastic systems; Bellman´s dynamic programming; HJB equations; Hamiltonian systems; Pontraygin´s maximum principle; modern optimal control theory; stochastic optimal controls; Calculus; Control systems; Differential equations; Dynamic programming; Jacobian matrices; Optimal control; Research and development management; Stochastic processes; Stochastic systems; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location
San Diego, CA
ISSN
0191-2216
Print_ISBN
0-7803-4187-2
Type
conf
DOI
10.1109/CDC.1997.652379
Filename
652379
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