Robust model predictive control for nonlinear systems

被引：0

作者：

Zhang Jun ^{[1
]}

Wang Biao ^{[1
]}

机构：

[1] Harbin Inst Technol, Sch Astronaut, Harbin 150001, Peoples R China

来源：

PROCEEDINGS OF THE 24TH CHINESE CONTROL CONFERENCE, VOLS 1 AND 2 | 2005年

关键词：

nonlinear systems; model predictive control; constraint inputs; stability; fuzzy model;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Robust model predictive control is proposed for a class of nonlinear systems with constraint inputs based on fuzzy T-S model. The upper bound of predictive cost is derived, constraints on stability and inputs are transformed into linear matrix inequalities (LMIs), which can easily be solved. The predictive controller is parallel distributed compensation (PDC) controller in the scheme. Sufficient conditions of moving horizon optimization are derived based on LMIs and Lvapunov funciton, stability of closed-loop systems is proved. The simulation results verify the effectiveness of the proposed method.

引用

页码：1127 / 1131

页数：5

共 11 条

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