Summary of the process identification workshop at the 1992 Canadian chemical engineering conference

Abstract

Abstract The highlights of the workshop can be summarized as follows: (1) The workshop reaffirmed that data prefiltering is a necessary step in the model building process in order to ensure nonstationary disturbances are not modelled as part of the process; (2) In addition, the workshop confirmed that improvements in the steady-state gain are seen if input test signals are carefully designed using the disturbance dynamics and the expected movement of the manipulated variables while under control as guides. As a result, the majority of input test signals should have significantly more power at low frequencies in order to improve the steady-state gain estimates; (3) Data prefiltering and input signal design decisions appear to affect the final model quality much more than the type of model structure used (Box-Jenkins, finite impulse response, frequency sampling filter); (4) Although the newer techniques presented by some of the university groups do not necessarily yield better quality models, they simplify the model building process by automating model building selections, or by providing better descriptions of model inadequacies.