%N 10
%J Automatica
%R 10.1016/j.automatica.2014.08.031
%A Panagiotis Patrinos
%A Pantelis Sopasakis
%A Haralambos Sarimveis
%A Alberto Bemporad
%K Stochastic model predictive control; Control of constrained systems; Stochastic switching systems
%D 2014
%L eprints2283
%X In this paper we study constrained stochastic optimal control problems for Markovian switching systems, an extension of Markovian jump linear systems (MJLS), where the subsystems are allowed to be nonlinear. We develop appropriate notions of invariance and stability for such systems and provide terminal conditions for stochastic model predictive control (SMPC) that guarantee mean-square stability and robust constraint fulfillment of the Markovian switching system in closed-loop with the {SMPC} law under very weak assumptions. In the special but important case of constrained {MJLS} we present an algorithm for computing explicitly the {SMPC} control law off-line, that combines dynamic programming with parametric piecewise quadratic optimization. 
%V 50
%I Elsevier 
%T Stochastic model predictive control for constrained discrete-time Markovian switching systems 
%P 2504-2514