Abstract
Control valve is a kind of essential terminal control component controlling the parameters of fluid such as flow and pressure in process-control. However it is a complex nonlinear, multi-input and single-output (MISO) system that is hard to model by traditional methodologies. To establish the pressure model of control valve, this paper presents a Hammerstein modeling method based on the least squares support vector machines (LS-SVM). The linear model parameters and the static nonlinearity of Hammerstein model can be obtained simultaneously by solving a set of linear equations followed by the singular value decomposition (SVD). As an example, a set of actual production data from a controlling system of chlorine in the salt chemistry industry were applied. The simulation results demonstrate that the obtained LS-SVM Hammerstein model can efficiently approximate the pressure of a control valve. Furthermore, the proposed LS-SVM Hammerstein model can be used in artificial intelligent control and the default diagnosis.
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