Predictive Control of a Multivariable Neutralisation Process Using Elman Neural Networks

被引：2

作者：

Wysocki, Antoni ^{[1
]}

Lawrynczuk, Maciej ^{[1
]}

机构：

[1] Warsaw Univ Technol, Inst Control & Computat Engn, Ul Nowowiejska 15-19, PL-00665 Warsaw, Poland

来源：

PROGRESS IN AUTOMATION, ROBOTICS AND MEASURING TECHNIQUES: CONTROL AND AUTOMATION | 2015年 / 350卷

关键词：

Process control; Model predictive control; Elman neural networks;

D O I：

10.1007/978-3-319-15796-2_34

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents development and simulation results of a computationally efficient predictive control algorithm based on a recurrent Elman neural network. The considered process is a multivariable neutralisation reactor. Process modelling and control issues are thoroughly discussed. In particular, the discussed computationally efficient predictive control algorithm with on-line trajectory linearisation and quadratic optimisation is compared to the truly nonlinear scheme with nonlinear optimisation repeated of each sampling instant on-line.

引用

页码：335 / 344

页数：10

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[J]. Adv. Intell. Sys. Comput., (335-344):
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