Robust State Estimation for a Class of Nonlinear Systems: Fuzzy-Model-Based LMI Approach

被引：0
|
作者：
He Guannan [1 ]
Jing Hongyu [1 ]
Ji Jing [2 ]
Yu Wensheng [3 ]
机构：
[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
[2] Guangdong Univ Technol, Coll Informat Engn, Guangzhou 510006, Guangdong, Peoples R China
[3] E China Normal Univ, Shanghai Key Lab Trustworthy Comp, Shanghai 200062, Peoples R China
来源：
2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年
关键词：
Robust; Nonlinear systems; Takagi-Sugeno (T-S) models; State estimation; Linear Matrix Inequalities (LMIs); FEEDBACK CONTROL DESIGN; STABILIZATION CONDITIONS; DYNAMIC-SYSTEMS; OBSERVERS;
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：
In this paper, we investigate the robust state estimation problem for a class of nonlinear dynamic systems described by Takagi-Sugeno (T-S) models. The main contribution of the proposed approach is to reconstruct the T-S models with unmeasurable premise variables into the uncertain T-S models and introduce the estimated state feedback to the models. The sufficient conditions for the convergence of the state estimation error are obtained based on the Lyapunov stability theory, and presented in terms of Linear Matrix Inequalities (LMIs). Finally, a numerical example is given to illustrate the effectiveness of the proposed approach.
引用
收藏
页码：3644 / 3648
页数：5
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