An industrial tool for identification and control of nonlinear valve characteristics

Abstract

This work presents an industrial system identification and control design tool in the context of nonlinear valve control as a typical problem in the refinery industry. A parametric SISO Hammerstein model structure is assumed. Two Hammerstein model identification approaches are implemented and integrated into an efficient tool: Prediction Error Minimization (PEM) as well as a closed-form method involving a Least-Squares and a Singular Value Decomposition part. Parameter uncertainty analysis methods are developed and presented. The second focus of the tool is to give comprehensive support in nonlinear control design and validation. For invertible static nonlinear maps, the Hammerstein structure can be transformed to a globally linear control design problem. This is exploited to design scheduled PID control laws. A series of tools for validation, closed-loop analysis, and tuning is developed and shown. The tool implementation is outlined and the functionality is demonstrated by a series of simulation results highlighting each major feature, based on artificially generated test data. The user is thus equipped with an efficient, state-of-the-art numerical tool to support control engineering for this class of nonlinear control problems.