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Robustness study on NARXSP-based stiction model

H., Zabiri and N., Mazuki (2009) Robustness study on NARXSP-based stiction model. In: 2009 International Conference on Signal Acquisition and Processing, 23 April 2009 through 5 April 2009;, Kuala Lumpur.

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Abstract

Stiction is the most commonly found valve problem in the process industry. Valve stiction may cause oscillations in control loops which increases variability in product quality, accelerates equipment wear and tear, or leads to system instability. In this paper, a series-parallel Recurrent Neural Network (NARXSP)-based stiction model is developed and its robustness against the uncertainty in the stiction parameters is tested under various conditions. It is shown that the NARXSP-based stiction model is robust when the stiction is less than 6% of the valve travel span

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Component; Control valve stiction, neural network, modeling Component; Control valve stiction, neural network, modeling
Subjects:T Technology > TP Chemical technology
Departments / MOR / COE:Departments > Chemical Engineering
ID Code:3736
Deposited By: Haslinda Zabiri
Deposited On:28 Dec 2010 07:03
Last Modified:19 Jan 2017 08:25

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