 |
|
|
|
|
|
|
||||||||||||||||||||||||||||||
|
|
|||||||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||||||||
|
|
|
|
|
|
 |
 |
|
|||
 |
 |
 |
|
||
 |
|
||||
 |
|
||||
|
|||||
 |
 |
|
|||
 |
 |
|
|||
|
|||||
The Model Based Control Strategy
Traditional PID Control uses feedback to adjust variables, such as furnace or oven temperature, pressure, or level, once a disruption is detected.
Model Based Control uses feedforward inputs to detect disruptions before they impact the process, and ensures the parameter is corrected before a problem exists. This is particularly effective in temperature applications where dead time, or lag time, is an issue or where it is difficult to maintain stable temeprature with PID.
The ACSI MBC creates models for each control/process variable and feedforward input. The ideal model then anticipates changes needed to maintain a consistent setpoint. This example screen shows a cross-section of a plug of glass as it exits a forehearth. The color gradient allows operators to quickly identify problems with homogeneity.
Once the optimum process is modeled, the ACSI model based controller
• Predicts control actions required to drive the parameter to setpoint quickly without overshoot.
• Continuously adapts to process and production changes for better control without loop tuning.
• Models feedforward inputs and updates control actions to quickly stabilize variation.
Click on any of these links to learn more about Model Based Control.
