A neural-network-based nonlinear controller using an extended Kalman filter

被引：4

作者：

Gao, FR ^{[1
]}

Wang, FL ^{[1
]}

Li, MZ ^{[1
]}

机构：

[1] Hong Kong Univ Sci & Technol, Dept Chem Engn, Kowloon, Peoples R China

来源：

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH | 1999年 / 38卷 / 06期

关键词：

D O I：

10.1021/ie980727k

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

A neural-network-based control scheme is presented to control unknown nonlinear dynamic processes. A multilayered feedforward neural network is used to model the process dynamics, and the control input is estimated by an extended Kalman filter based on the neural model. The effectiveness of the proposed scheme is verified by both simulations and experiments.

引用

页码：2345 / 2349

页数：5

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