It is generally accepted that the health of
proportional-integral-derivative (PID) loops and model
predictive control (MPC) has a direct impact on a plants
bottom line. Improved process control has been proven to reduce
variability, increase product quality and yields, and reduce
energy costs as well as raw material usage. The question, then,
is this: How can a work process be developed to support this
effort and maintain controller performance?