453150 Leveraging Simulation and Experiment in Process-Control Education and Training: Case Study of Development of Educational Software Suites for Either Stand-Alone Study or in Conjunction with Laboratory Measurements
Thursday, November 17, 2016: 10:54 AM
Continental 2 (Hilton San Francisco Union Square)
Extended Abstract: File Not Uploaded
Laboratory experiments to demonstrate the underlying principles of process control can sometimes challenge scalability for larger classes/sessions, through comparative lack of feasibility given time constraints. The primary aims of the laboratory were to allow students gain an understanding of feedback control, the typical characteristics associated with P, PI and PID controllers and introduce the concept of a transfer function for a system and how one might determine it. An important objective of this project was to rectify this by conducting a critical reappraisal of a control apparatus and experiment at UCD Chemical Engineering. In particular, changes introduced included: (a) reducing the number of set point changes in experiments, (b) increasing the set point change from 10% to 20% in the case of proportional controller experiments to emphasis the difference between different proportional band settings, using disturbances as opposed to set point changes when demonstrating derivative action, and (c) using 30% proportional band as opposed to 5% proportional band when using a PID controller to improve control loop stability. These changes have resulted in total experiment time being reduced from by a quarter. 201 minutes to 153 minutes.
A second major theme lies in the incorporation of process-control simulation into the physical laboratories, to develop a learning tool to supplement a process control laboratory. A code was generated within MATLAB, which could generate a transfer function from an open-loop step response recorded in the laboratory. A simulation model was created in an application within MATLAB called Simulink. This allowed for a simulation of the laboratory control settings and a comparison of real and simulated data. The calibration of this was limited due to a lack of replication of experimental data; however the model itself functions as was intended. Due to a lack of certainty within the laboratory results, a simulation exercise to demonstrate the characteristics of the PID controller was created and shows promising potential as a stand-alone control-simulation environment, or for use with laboratory efforts.