Approximation to a class of non-autonomous systems by dynamic fuzzy inference marginal linearization method

被引：10
|
作者：
Wang, De-Gang [1 ,2 ]
Song, Wen-Yan [3 ]
Shi, Peng [4 ,5 ]
Li, Hong-Xing [1 ]
机构：
[1] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
[2] Informedia Elect Co Ltd, Dalian 116001, Peoples R China
[3] Dongbei Univ Finance & Econ, Dept Quantitat Econ, Dalian 116025, Peoples R China
[4] Victoria Univ, Sch Sci & Engn, Melbourne, Vic 8001, Australia
[5] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia
来源：
INFORMATION SCIENCES | 2013年 / 245卷
基金：
中国国家自然科学基金;
关键词：
Fuzzy inference; Fuzzy system; Non-autonomous system; Universal approximators; LINEAR RULE CONSEQUENT; UNIVERSAL APPROXIMATORS; NONLINEAR-SYSTEMS; SUFFICIENT CONDITIONS; LMI APPROACH; STABILIZATION; DESIGN; SETS;
D O I：
10.1016/j.ins.2013.05.011
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, a dynamic fuzzy inference marginal linearization (DFIML) method is proposed for modeling nonlinear dynamic systems. This method can transfer a group of input-output data into a time-variant fuzzy system with variable coefficients. It is shown that solutions of time-variant fuzzy systems generalized by DFIML method are universal approximators to solutions of a class of non-autonomous systems. Also the analytical solutions of these time-variant fuzzy systems can be obtained. Finally, a simulation example is provided to illustrate the validity and potential of the developed techniques. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码：197 / 217
页数：21
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