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Modeling and control of pH neutralization using neural network predictive controller

S.B., Hisham and M.G.M.K., Elarafi (2008) Modeling and control of pH neutralization using neural network predictive controller. In: 2008 International Conference on Control, Automation and Systems, ICCAS 2008, 14 October 2008 through 17 October 2008, Seoul.

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Abstract

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<sup>+</sup>] 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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Backpropagation; Electric control equipment; Functions; Hydrogen; Mathematical models; Model predictive control; Neural networks; Predictive control systems; Proportional control systems; Quality control; Three term control systems; Time varying control systems; Two term control systems; Artificial neural network; Control strategies; Dead times; Empirical models; Empirical techniques; Hydrogen ions; Intelligent process control; Logarithmic relationships; Modeling and controls; Neutralization processes; Non linearities; PID controllers; Predictive controllers; Process control
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Departments > Electrical & Electronic Engineering
ID Code:421
Deposited By: Suhaila Badarol Hisham
Deposited On:09 Mar 2010 01:09
Last Modified:19 Jan 2017 08:26

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