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Event-triggered deadtime estimation from closed-loop data

Our objective is to estimate process deadtime, based on normal operating data only. The first issue is to examine data to find intervals with sufficient excitation for identification. We conclude that the only useful event to hope for is a significant enough change in setpoint. A method is then proposed for finding the transient parts of data after setpoint changes. A deadtime estimation method based on Laguerre models and a rational approximation for the deadtime is then applied to the selected data. The method has been tested extensively via simulation as well as on real industrial data, and found to give very satisfactory results.