Neural predictive control by instantaneous linearization

被引：0

作者：

Lamanna, Rosalba ^{[1
]}

Gimon, Raquel ^{[1
]}

机构：

[1] Univ Simon Bolivar, Dept Proc Sistemas, Caracas 1081A, Venezuela

来源：

REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL | 2007年 / 4卷 / 02期

关键词：

neural control; predictive control; neural networks; instantaneous linearization; pH control;

D O I：

10.1016/S1697-7912(07)70213-3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A Generalized Predictive Control scheme (GPC) is developed, based on a neural model of the process, and then applied on a laboratory neutralization reactor. The neural model, which is obtained previously by identification, is linearized at each iteration of the control algorithm. Hence, the learning capacity of the neural networks and the computer efficiency of the GPC are combined, producing a system with the advantages of a predictive controller extended to non-linear systems, that shows good precision and transient response performance. Copyright (C) 2007 CEA-IFAC.

引用

页码：90 / +

页数：9

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