(37b) Oscillatory Control Loops: The Lost Economic Benefits. Can Anything Be Done?

In chemical, refining, and petrochemical processing industries, competitive pressure, prohibitively increasing costs of energy and tighter environmental regulations make it imperative to explore various avenues to identify potential areas of improvement. Identifying trends that lead to performance degradation is also important in carrying out preventative maintenance. Various literature on the performance of control loops revealed that as many as 60% of all industrial controllers have some kind of performance problem (Bialkowski, 1993; Ender, 1993; Rinehart, 1997). Studies in controller performance monitoring show that many control loops in the process industry perform poorly because of bad tuning or equipment problems; however, control valve nonlinearities are the major contributors towards performance degradation (Beckman and Jury, 1997; Isermann and Raab, 1993; Ruel, 2000; Corradini and Orlando, 2002). The control valve problems account for about 32% of ??poor'' or ??failed'' control loops (Miller and Desborough, 2001). A survey (Yang and Clarke, 1999) indicated that 30% of all control loops in Canadian paper mills were oscillating because of valve problems. Limit cycles due to valve problems were identified in many refineries, causing a large variation in the final products (Ruel,2000). Oscillations in control loops increase variability in product quality, accelerate equipment wear, and may cause other issues that could potentially disrupt the operation. In more than 4000 audited loops in all industries as reported by Beckman and Jury (1997), it was found that performance for more than 50% of the control loops could be significantly improved if the control loop hardware (control valves, I/P converters) were serviced at appropriate times, regularly. Since there are several possible causes for performance degradation of control loops, it is not always easy to improve their performance by taking corrective action, as it is a challenging task to identify the root cause. Hence, detection and diagnosis of oscillatory behavior in control loop is of paramount importance in order to take appropriate corrective action.

In recent years, significant research has been performed on control loop oscillation diagnosis; there are still many unresolved issues such as indecisive or wrong diagnostics for certain regions of process dynamics, failure in the case of multiple faults occurring simultaneously and, absence of quantification of root-cause. In this work, a novel methodology has been devised to bridge these gaps in oscillation diagnosis. Power spectral density (PSD) and Auto Correlation Function (ACF) based oscillation detection method followed by a model based approach for identifying and quantifying the root cause of the oscillations is proposed. The application of each component of the algorithm is described with appropriate example cases. Finally, overall methodology is validated on industrial and simulation case studies for various cases of stiction, poor controller tuning, and external disturbances.

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