Neural Network Modeling of Valve Stiction Dynamics

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, we present a new approach in control
valve stiction modeling using Recurrent Neural-Network with
NARX structure. It is shown that the performance of the
developed model is comparable to other models reported in
literature.