Neural Network Based pH Control of a Weak Acid - Strong Base System

被引：0
作者：
Tharakan, Liny Geevarghese
Benny, Anish
Jaffar, N. E.
Jaleel, J. Abdul
机构：
来源：
2013 IEEE INTERNATIONAL MULTI CONFERENCE ON AUTOMATION, COMPUTING, COMMUNICATION, CONTROL AND COMPRESSED SENSING (IMAC4S) | 2013年
关键词：
Artificial Neural Network; Neural Network Model Predictive Control; pH Control; Weak Acid - Strong Base System;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
pH neutralization is a difficult process to be controlled due to the nonlinear and time-varying process characteristics. Model Predictive Control appeared in industry as an effective means to deal with multivariable constrained control problems. This paper does the study of the pH neutralization process of a weak acid - strong base system using a neural network model predictive control technique. The simulation results are analyzed for step and random acid disturbances, which shows that the controller controls the pH within the required limits with less mean square error.
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页码：674 / 679
页数：6
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