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On Infinite Linear Programming and the Moment Approach to Deterministic Infinite Horizon Discounted Optimal Control Problems

Author(s):

A. Kamoutsi, T. Sutter, P. Mohajerin Esfahani, J. Lygeros
Conference/Journal:

IEEE Control Systems Letters, vol. 1, no. 1, pp. 134-139, (arXiv:1703.09005)
Abstract:

We revisit the linear programming approach to deterministic, continuous time, infinite horizon discounted optimal control problems. In the first part, we relax the original problem to an infinite-dimensional linear program over a measure space and prove equivalence of the two formulations under mild assumptions, significantly weaker than those found in the literature until now. The proof is based on duality theory and mollification techniques for constructing approximate smooth subsolutions to the associated Hamilton-Jacobi- Bellman equation. In the second part, we assume polynomial data and use Lasserre’s hierarchy of primal-dual moment- sum-of-squares semidefinite relaxations to approximate the value function and design an approximate optimal feedback controller. We conclude with an illustrative example.

Year:

2017
Type of Publication:

(01)Article
Supervisor:



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@ARTICLE{7936567, 
author={A. Kamoutsi and T. Sutter and P. Mohajerin Esfahani and J. Lygeros}, 
journal={IEEE Control Systems Letters}, 
title={On Infinite Linear Programming and the Moment Approach to Deterministic Infinite Horizon Discounted Optimal Control Problems}, 
year={2017}, 
volume={1}, 
number={1}, 
pages={134-139}, 
keywords={Aerospace electronics;Atmospheric measurements;Extraterrestrial measurements;Linear programming;Mathematical model;Optimal control;Particle measurements;Optimal control;discounted occupation measures;infinite linear programming;moments;sum-of-squares}, 
doi={10.1109/LCSYS.2017.2710234}, 
ISSN={2475-1456}, 
month={July},}
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