FUZZY ROBUST CONSTRAINED MODEL PREDICTIVE CONTROL FOR NONLINEAR SYSTEMS

被引：28
|
作者：
Chang, Xiao-Heng [1 ]
Yang, Guang-Hong [2 ]
机构：
[1] Bohai Univ, Coll Informat Sci & Engn, Jinzhou 121003, Peoples R China
[2] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Peoples R China
来源：
ASIAN JOURNAL OF CONTROL | 2011年 / 13卷 / 06期
关键词：
Model predictive control; T-S fuzzy systems; uncertainties; constraints; linear matrix inequalities; STABILITY CONDITIONS;
D O I：
10.1002/asjc.221
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper addresses robust constrained model predictive control (MPC) for a class of nonlinear systems with structured time-varying uncertainties. First, the Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear system. Then, we develop some techniques for designing fuzzy control which guarantees the system stabilization subject to input and output constraints. Both parallel and nonparallel distributed compensation control laws (PDC and non-PDC) are considered. Sufficient conditions for the solvability of the controller design problem are given in the form of linear matrix inequalities. A simulation example is presented to illustrate the design procedures and performances of the proposed methods.
引用
收藏
页码：947 / 955
页数：9
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