Robust Model Predictive Control With Integral Sliding Mode in Continuous-Time Sampled-Data Nonlinear Systems

被引:175
作者
Rubagotti, Matteo [1 ]
Raimondo, Davide Martino [2 ]
Ferrara, Antonella [3 ]
Magni, Lalo [3 ]
机构
[1] Univ Trento, Dept Mech & Struct Engn, I-38123 Trento, Italy
[2] Swiss Fed Inst Technol, Automat Control Lab, CH-8092 Zurich, Switzerland
[3] Univ Pavia, Dept Comp Engn & Syst Sci, I-27100 Pavia, Italy
关键词
Constrained control; nonlinear predictive control (NPC); sampled data control; sliding mode control (SMC); stability of nonlinear systems; TO-STATE STABILITY; INPUT; DESIGN;
D O I
10.1109/TAC.2010.2074590
中图分类号
TP [自动化技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
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.
引用
收藏
页码:556 / 570
页数:15
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