Finding the source of nonlinearity in a process with plant-wide oscillation

Published versio

Diagnosis of a unit-wide disturbance caused by saturation in a manipulated variable

It is well known that faulty control valves with friction in the moving parts lead to limit cycle oscillations which can propagate to other parts of the plant. However, a control loop with healthy valve can also undergo oscillatory behavior. The root cause of a unit-wide oscillation in a distillation column was traced to a pressure control loop in a case study at Mitsui Chemicals. The diagnosis was made by means of a new technique of pattern matching of the time-resolved frequency spectrum using a wavelet analysis tool. The method identified key characteristics shared by measurements at various places in the column and quantified the similarities. Non-linearity was detected in the time trend of the pressure measurement, a result which initially suggested the root cause was a faulty actuator or sensor. Further analysis showed, however, that the source of non-linearlity was periodic saturation of the manipulated variable caused by slack tuning. The problem was remidied by changing the controller tuning settings and the unit-wide disturbance then went away

Detection of distributed oscillations and root-cause diagnosis

7-8 June 200

Root cause isolation of propagated oscillations in process plants

Persistent whole-plant disturbances can have an especially large impact on product quality and running costs. There is thus a motivation for the automated detection of a plant-wide disturbance and for the isolation of its sources. Oscillations increase variability and can prevent a plant from operating close to optimal constraints. They can also camouflage other behaviour that may need attention such as upsets due to external disturbances. A large petrochemical plant may have a 1000 or more control loops and indicators, so a key requirement of an industrial control engineer is for an automated means to detect and isolate the root cause of these oscillations so that maintenance effort can be directed efficiently. The propagation model that is proposed is represented by a log-ratio plot, which is shown to be ‘bell’ shaped in most industrial situations. Theoretical and practical issues are addressed to derive guidelines for determining the cut-off frequencies of the ‘bell’ from data sets requiring little knowledge of the plant schematic and controller settings. The alternative method for isolation is based on the bispectrum and makes explicit use of this model representation. A comparison is then made with other techniques. These techniques include nonlinear time series analysis tools like Correlation dimension and maximal Lyapunov Exponent and a new interpretation of the Spectral ICA method, which is proposed to accommodate our revised understanding of harmonic propagation. Both simulated and real plant data are used to test the proposed approaches. Results demonstrate and compare their ability to detect and isolate the root cause of whole plant oscillations. Being based on higher order statistics (HOS), the bispectrum also provides a means to detect nonlinearity when oscillatory measurement records exist in process systems. Its comparison with previous HOS based nonlinearity detection method is made and the bispectrum-based is preferred

A comparative study of several control techniques applied to a boost converter

In this paper a comparison among three control strategies is presented, with application to a boost DC-DC converter. The control strategies are developed on the switched boost circuit model and validated on the nonlinear model by use of simulations. The classical PID, a 2dof-IMC (two degree of freedom internal model controller) and an alternative controller - MAC (uprocessor advanced control) are applied, tested and compared on the nonlinear system. Additional tests show the robustness of the controllers on the highly nonlinear circuit