Stiction is the most common problem in pneumatic control valves, which are widely used in the process industry. Stiction causes fluctuation of process variables, which lowers productivity. Therefore, developing a method to detect stiction and distinguish it from other causes is crucial to help operators take an appropriate action for improving control performance. The present work proposes a valve stiction model and new stiction detection algorithms. Using only two parameters, the proposed model can describe the stiction phenomenon with sufficient accuracy. The usefulness of the proposed detection methods are demonstrated by comparing them with a conventional method. The proposed methods are shown to successfully detect valve stiction, distinguish it from bad tuning or disturbances, and quantify the degree of stiction, by using simulation data sets and real operation data sets of several chemical processes. Copyright c 2004 IFAC
Control performance monitoring is an important technology to keep highly efficient operation of production plants.Bad control performance is caused mainly by inadequate controller tuning or equipment malfunction. Valve Stiction is the most common problem in pneumatic control valves, which are widely used in the process industry.Stiction causes persistent fluctuation of process variables. Therefore, developing a method to detect stiction andd distinguish it from inadequate controller tuning is crucial to help operators take an appropriate action for improving control performance. In the present work, valve stiction is modeled by taking into account its physical mechanism, and then new stiction detection algorithms are proposed. The usefulness of the proposed detection methods are demonstrated by comparing them with conventional methods. It is shown that the proposed methods can successfully detect valve stiction, distinguish it from had tuning or disturbances, and quantify the degree of stiction, by using simulation data sets and real operation data sets obtained from several chemical processes.
In the challenge to manufacture high quality products it is necessary to regularly monitor performance of control loops that regulate the quality variables of interest. This paper describes a unified approach of the control performance and the PID controller design which are based on the above control strategy. According to the proposed approach, the control performance is first monitored regularly. If the performance exceeds a user-defined threshold, the system identification is initiated and PID parameters are subsequently updated for the new model. Optimal PID parameters are calculated based on the LQG trade-off curve obtained for the re-identified process model. The behavior of the proposed scheme is evaluated by applying for real chemical processes.
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