Ask Greg McMillan

Greg's Response:

Essentially all processes are nonlinear where the open loop gain, time constants, and dead times change with operating conditions. These changes are generally quite large for changes in production rates and deterioration in unit operations (e.g., catalyst activity, fouling, plugging, …). First principle dynamic models can identify the consequential changes in process dynamics. This knowledge can be used in adaptive PID tuning. For production rate, the update may be simply based on feed rate. For degradation in unit operations, changes in loop dynamics identified in the models can be used to update the PID tuning settings. The knowledge needed can be rapidly gained by running dynamic models much faster than real time (e.g., 100x real time). The results can be tested in a Digital Twin with the actual control system that is running somewhat faster than real time (e.g., 10x real time). There also the possibility of a dynamic simulation running in sync with the PID to update the tuning settings more continuously. First principles dynamic models can be used to implement adaptive PID Tuning and improve process operating conditions.