TY  - JOUR
PB  - Elsevier 
SN  - 0005-1098
VL  - 50
A1  - Patrinos, Panagiotis
A1  - Sopasakis, Pantelis
A1  - Sarimveis, Haralambos
A1  - Bemporad, Alberto
N2  - 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. 
EP  - 2514
TI  - Stochastic model predictive control for constrained discrete-time Markovian switching systems 
SP  - 2504
KW  - Stochastic model predictive control; Control of constrained systems; Stochastic switching systems
ID  - eprints2283
Y1  - 2014/10//
JF  - Automatica
AV  - none
IS  - 10
UR  - http://www.sciencedirect.com/science/article/pii/S0005109814003471
ER  -