@inproceedings{07ee6d8bba4e4dba91c34ed016cad71a,
title = "A multi-step robust model predictive control scheme for polytopic uncertain multi-input systems",
abstract = "Model predictive control (MPC) has attracted wide attention in process industries with its ability to handle constrained multivariable processes. Computational complexity can become a limiting factor when MPC is applied to large-scale systems with fast sampling times. In this paper, a control scheme known as multi-step robust MPC is presented for polytopic uncertain multi-input systems. Only one or several state feedback laws are optimized at each time interval to reduce computational complexity. A set invariance condition for polytopic uncertain systems is identified and the invariant set is determined by solving a linear matrix inequality (LMI) optimization problem. Based on the set invariance condition, a min-max multi-step robust MPC scheme is proposed. Numerical simulations show the effectiveness of the proposed scheme.",
author = "Langwen Zhang and Jingcheng Wang and Bohui Wang",
note = "Publisher Copyright: {\textcopyright} IFAC.; 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 ; Conference date: 24-08-2014 Through 29-08-2014",
year = "2014",
doi = "10.3182/20140824-6-za-1003.02207",
language = "英语",
series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",
publisher = "IFAC Secretariat",
pages = "8540--8545",
editor = "Edward Boje and Xiaohua Xia",
booktitle = "19th IFAC World Congress IFAC 2014, Proceedings",
}