On Stability and Performance of Stochastic Predictive Control Techniques

Abstract

This article is concerned with stability and performance of controlled stochastic processes under receding horizon policies. We develop a framework for systematically guaranteeing 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 examples.