Stability and performance of stochastic predictive control
Systems and Control
2017-11-27 v2 Optimization and Control
Abstract
This article is concerned with stability and performance of controlled stochastic processes under receding horizon policies. We carry out a systematic study of methods to guarantee stability under receding horizon policies via appropriate selections of cost functions in the underlying finite-horizon optimal control problem. We also obtain quantitative bounds on the performance of the system under receding horizon policies as measured by the long-run expected average cost. The results are illustrated with the help of several simple examples.
Cite
@article{arxiv.1304.2581,
title = {Stability and performance of stochastic predictive control},
author = {Debasish Chatterjee and John Lygeros},
journal= {arXiv preprint arXiv:1304.2581},
year = {2017}
}
Comments
19 pages. Minor corrections and updated references