Stability and performance of stochastic predictive control
arXiv:1304.2581 · doi:10.1109/TAC.2014.2335274
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.
19 pages. Minor corrections and updated references