An approximate dynamic programming approach to probabilistic reachability for stochastic hybrid systems

Author

Abate, Alessandro ; Prandini, Maria ; Lygeros, John ; Sastry, Shankar

Author_Institution

Stanford Univ., Stanford, CA, USA

fYear

2008

fDate

9-11 Dec. 2008

Firstpage

4018

Lastpage

4023

Abstract

This paper addresses the computational overhead involved in probabilistic reachability computations for a general class of controlled stochastic hybrid systems. An approximate dynamic programming approach is proposed to mitigate the curse of dimensionality issue arising in the solution to the stochastic optimal control reformulation of the probabilistic reachability problem. An algorithm tailored to this problem is introduced and compared with the standard numerical solution to dynamic programming on a benchmark example.

Keywords

approximation theory; dynamic programming; numerical analysis; optimal control; probability; reachability analysis; stochastic systems; approximate dynamic programming approach; dynamic programming approach; numerical solution; probabilistic reachability; probabilistic reachability computations; stochastic hybrid systems; stochastic optimal control reformulation; Context modeling; Control systems; Cost function; Dynamic programming; Optimal control; Safety; State-space methods; Stochastic processes; Stochastic systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2008. CDC 2008. 47th IEEE Conference on

Conference_Location

Cancun

ISSN

0191-2216

Print_ISBN

978-1-4244-3123-6

Electronic_ISBN

0191-2216

Type

conf

DOI

10.1109/CDC.2008.4739410

Filename

4739410