Taking control with your DCS
In this article, Hank A. Britain, director of optimisation and advanced control at OpX Control, reveals how the base control layer can be improved to reduce variability, and how many advanced process control (APC)-type functions can be done in the distributed control system (DCS), leading to improved control in ethanol plants.
Part I: Begin with the base layer
In a book published by the International Society of Automation (ISA) on advanced control, Blevins et. al. state: “Proper controller tuning is the largest, quickest, and least expensive improvement one can make in the basic control system to decrease process variability.”1
Proper tuning involves a model-based method such as lambda tuning. Model-based tuning is less time-consuming, less disruptive to the process, and provides far superior results as opposed to ‘trial-and-error’ methods. Learn about the process Process testing is the key to modelbased tuning. Using mathematical relationships, the learning is passed on to the proportional-integral-derivative (PID) controller.
Figure 1 shows a typical step test applied to learn about the process. The value of the model is explained below....
Part I: Begin with the base layer
In a book published by the International Society of Automation (ISA) on advanced control, Blevins et. al. state: “Proper controller tuning is the largest, quickest, and least expensive improvement one can make in the basic control system to decrease process variability.”1
Proper tuning involves a model-based method such as lambda tuning. Model-based tuning is less time-consuming, less disruptive to the process, and provides far superior results as opposed to ‘trial-and-error’ methods. Learn about the process Process testing is the key to modelbased tuning. Using mathematical relationships, the learning is passed on to the proportional-integral-derivative (PID) controller.
Figure 1 shows a typical step test applied to learn about the process. The value of the model is explained below....
Loading ...
