Control Loop Performance Assessment. 2. Hammerstein Model Approach for Stiction Diagnosis

Abstract

In part 2 of this two-part series, an approach for diagnosis and quantification of stiction using a simple single-parameter model is proposed. The stiction model, in conjunction with an identified process model from routine operating data, is shown to successfully facilitate stiction diagnosis. An optimization approach is used to jointly identify the process model and the stiction parameter. This approach is based on the identification of a Hammerstein model of the system comprising the sticky valve and the process. In this work, a new identification procedure for Hammerstein systems that supports stiction diagnosis is proposed. Industrial and simulation case studies are shown to demonstrate the application of the proposed approach for diagnosing stiction.

RETRACTED: Review on Valve Stiction. Part I: From Modeling to Smart Diagnosis

“…Srinivasan et al [62] fitted OP and PV datasets to a Hammerstein model defined also by the nonlinear Stenman's model [28] plus a linear ARMAX model. A grid search algorithm was used to determine the single parameter of the stiction model, while the process parameters were computed through separable least-squares method.…”

“…Choudhury et al [25] improved the approach of Srinivasan et al [62] by using their own stiction model [10], since the single parameter stiction model [28] was proved to be not able to capture the real stiction behavior. A two-dimensional grid search method was used to estimate both the stiction and the process model parameters.…”

“…The method developed by Srinivasan et al [62] was used to detect and estimate stiction, while the nonparametric transform was used to distinguish oscillations occurring due to marginally stable control loop and external disturbances.…”

“…The problem is addressed integrating a multiple oscillation detection algorithm [72], a model based stiction estimation [62], and additional information obtained by analyzing the data-driven model obtained from Hammerstein method.…”

On-line wavelet estimation of Hammerstein system nonlinearity

“…The Hammerstein system ( Fig. 1), being a cascade of a memoryless nonlinearity followed by a linear dynamics, is a popular nonlinear system modeling tool and has already found applications in several areas, e.g., automatic control, signal processing, economy, chemistry, and biomedical engineering, see the works of Coca and Billings (2001), Chen et al (1989), Srinivasan et al (2005), Nordsjo and Zetterberg (2001), Giannakis and Serpedin (2001) and the exhaustive reference set therein). Example 1.…”