TY  - JOUR
VL  - 56
IS  - 3
JF  - IEEE Transactions on Automatic Control 
Y1  - 2011/03//
SP  - 556 
PB  - IEEE 
A1  - Rubagotti, Matteo
A1  - Raimondo, Davide Martino
A1  - Ferrara, Antonella
A1  - Magni, Lalo
EP  - 570
ID  - eprints1208
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5570914&isnumber=5725246
KW  - 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
TI  - Robust model predictive control with integral sliding mode in continuous-time sampled-data nonlinear systems
AV  - none
N2  - 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.
SN  - 0018-9286
ER  -