ON-Line Nonlinear Systems Identification of Coupled Tanks via Fractional Differential Neural Networks

被引：13

作者：

Boroomand, Arefeh ^{[1
]}

Menhaj, Mohammad Bagher ^{[1
]}

机构：

[1] Amir Kabir Univ Technol, Dept Elect Engn, Tehran 15914, Iran

来源：

CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年

关键词：

Fractional Differential Neural Networks (FDNNs); Nonlinear System identification; State Estimation; Coupled Tanks;

D O I：

10.1109/CCDC.2009.5191572

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

fractional differential neural network (FDNN) is the extended neural network using fraction a I-order operators. On-line nonlinear system identification using FDNN is studied in this paper. Here all states of the non-linear system are assumed to be available in the system output. Through Lyapunov-like analysis, the fractional neural network parameters are adjusted so it will be proven that the identification error becomes bounded and tends to zero. To illustrate the applicability of the FDNN as a nonlinear identifier, two coupled tanks are considered as a case study. The results of simulation are very promising.

引用

页码：2185 / 2189

页数：5

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