Solving the Hamilton-Jacobi-Bellman equation for a stochastic system with state constraints
Paper i proceeding, 2014

We present a method for finding a stationary solution to the Hamilton-Jacobi-Bellman (HJB) equation for a stochastic system with state constraints. A variable transformation is introduced which turns the HJB equation into a combination of an eigenvalue problem, a set of partial differential equations (PDEs), and a point-wise equation. As a result the difficult infinite boundary conditions of the original HJB becomes homogeneous. To illustrate, we numerically solve for the optimal control of a Linear Quadratic Gaussian (LQG) system with state constraints. A reasonably accurate solution is obtained even with a very small number of collocation points (three in each dimension), which suggests that the method could be used on high order systems, mitigating the curse of dimensionality. Source code for the example is available online.

Författare

Torsten Wik

Chalmers, Signaler och system, System- och reglerteknik

Claes Breitholtz

Chalmers, Signaler och system, System- och reglerteknik

Proceedings of the IEEE Conference on Decision and Control

07431546 (ISSN) 25762370 (eISSN)

Vol. 2015-February 1840-1845

Ämneskategorier

Beräkningsmatematik

Reglerteknik

Fundament

Grundläggande vetenskaper

DOI

10.1109/CDC.2014.7039666

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Senast uppdaterat

2024-07-18