%J IEEE Transactions on Automatic Control 
%N 3
%R 10.1109/TAC.2010.2074590
%A Matteo Rubagotti
%A Davide Martino Raimondo
%A Antonella Ferrara
%A Lalo Magni
%K closed-loop system; continuous-time sampled-data nonlinear uncertain systems; input-to-state practical stability; integral sliding mode control; robust model predictive control; stability; closed loop systems; continuous time systems; nonlinear control systems; predictive control; robust control; sampled data systems; uncertain systems; variable structure systems
%L eprints1208
%D 2011
%X This paper proposes a control strategy for nonlinear constrained continuous-time uncertain systems which combines robust model predictive control (MPC) with sliding mode control (SMC). In particular, the so-called Integral SMC approach is used to produce a control action aimed to reduce the difference between the nominal predicted dynamics of the closed-loop system and the actual one. In this way, the MPC strategy can be designed on a system with a reduced uncertainty. In order to prove the stability of the overall control scheme, some general regional input-to-state practical stability results for continuous-time systems are proved.
%V 56
%I IEEE 
%T Robust model predictive control with integral sliding mode in continuous-time sampled-data nonlinear systems
%P 556 -570