Revised binary tree data-driven model for valve stiction

Valve Stiction is a common nonlinear phenomenon in pneumatic control valves and it causes oscillations in the control loops. A model of valve stiction that is easy to implement and accurate is desired for analysis of this phenomenon. Compared with the physical model, the data-driven model does not require excess knowledge on various physical parameters, thus it is widely used in modeling and diagnosis of valve stiction behavior. In this paper, modifications are made to the Two-layer binary tree data-driven model to overcome its shortcomings on handling instantaneous input command on reverse motion. It has simpler logic structure compared with recent proposed XCH model. Accuracy of the revised binary tree model is then tested and validated by ISA control valve standard test.