Commissioning Control Systems – Process Delay

by Bill Fester on August 29, 2011

in DCS, Industries, Paper

from Modeling And Control

by Terry Blevins

Single-loop and multi-loop control may be used to address a wide variety of control requirements. However, if a process is characterized by extremely long process delays or by a high degree of process interaction, then other control techniques may be required.
The control of quality parameters such as composition is often complicated by large process delays. One example of this in Chapter 16 of Control Loop Foundation – Batch and Continuous Processes, of a process that is characterized by large process delay is the bleaching area of a paper pulp mill. As is illustrated below, in this area of the pulp mill, bleaching chemicals are used to achieve a desired level of pulp brightness.

Since the reaction after chemical addition is very slow, the bleach tower is designed for long residence times. Because of the transport delay associated with the bleach tower, a brightness measurement made after the bleach tower may not reflect a change in bleaching chemical addition for 30–60 minutes depending on the pulp feedstock flow rate. To account for changes in the feedstock consistency, that is, changes in solids (“dry stock”) concentration, and feedstock flow rate, the bleaching chemical addition rate may be set by ratio control of chemical/dry stock. However, to effectively adjust this ratio based on deviations of brightness from setpoint, it is necessary to use a control technique such as MPC that accounts for the very long process delay.

This improvement over PID feedback control performance is possible because the MPC algorithm is generated based on process response to a step change in process inputs, known as the step response model, rather than the algorithm being pre-defined as is the case with PID algorithm. When a change is made in an input of a process characterized by deadtime, unlike the PID algorithm the MPC algorithm is aware that this change will not be immediately reflected in the process. This awareness of the process response allows the MPC algorithm to do a better job of controlling deadtime-dominant processes.

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