On Computation of Optimal Switching HJB Equation

Author

Zhang, Huan ; James, Matthew R.

Author_Institution

Dept. of Eng., Australian Nat. Univ., Canberra, ACT

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

2704

Lastpage

2709

Abstract

This paper proposes an algorithm to compute the optimal switching cost from the dynamic programming Hamilton-Jacobi-Bellman (HJB) equations. For the optimal switching control problem, the HJB equation is a system of quasi-variational inequalities (SQVIs) coupled by a nonlinear operator. By exploring the fundamental limit on the number of switches could occur in an optimal switching control signal and making use of the connections with the optimal stopping control problem, the coupled SQVIs are decoupled into a sequence of optimal stopping type quasi-variational inequalities (QVIs). The optimal stopping QVIs are solved by the approach of Markov chain approximation

Keywords

Markov processes; approximation theory; dynamic programming; optimal control; time-varying systems; Hamilton-Jacobi-Bellman equations; Markov chain approximation; dynamic programming; optimal stopping control; optimal switching control; optimal switching cost; quasi-variational inequalities; Control systems; Cost function; Couplings; Dynamic programming; Nonlinear equations; Optimal control; Partial differential equations; Switched systems; Switches; USA Councils;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2006 45th IEEE Conference on

Conference_Location

San Diego, CA

Print_ISBN

1-4244-0171-2

Type

conf

DOI

10.1109/CDC.2006.377594

Filename

4177187