By Topic

Modeling and control of pH neutralization using neural network predictive controller

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Elarafi, M. ; Electr.&Electron. Eng. Dept., Univ. Teknol. PETRONAS, Tronoh ; Hisham, S.B.

The difficulty of controlling pH neutralization processes resides in the non-linearity of such processes. This behavior is due to the logarithmic relationship between the hydrogen ions concentrations [H+] and the level of pH. The control strategy to be developed very much depends on the feasibility of the mathematical model that represents the process. This paper illustrates feasible modeling of the pH neutralization plant using empirical techniques and investigates the performance of an artificial neural network predictive controller against the more traditional PID controllers. As a conclusion, a feasible empirical model was found closest to a second-order with dead time. The artificial neural network predictive controller has outperformed the conventional PI /PID controllers.

Published in:

Control, Automation and Systems, 2008. ICCAS 2008. International Conference on

Date of Conference:

14-17 Oct. 2008