Extension of IMC tuning correlations for non-self regulating (integrating) processes

Area of Science:

• Control Engineering
• Process Control

Background:

• PID with Filter controllers mitigate measurement noise in derivative action, reducing controller output travel and final control element wear.
• Internal Model Control (IMC) tuning correlations exist for PI, PID, and PID with Filter controllers in self-regulating processes.
• Existing IMC correlations do not cover PID with Filter controllers for non-self-regulating (integrating) processes.

Purpose of the Study:

• To develop and present novel IMC tuning correlations for PID with Filter controllers applied to non-self-regulating processes.
• To provide a complete set of IMC tuning correlations for PI, PID, and PID with Filter controllers across different process types.
• To offer an alternative to fixed-ratio tuning methods by calculating filter time constants based on process models.

Main Methods:

• Extension of existing IMC tuning framework to include PID with Filter controllers for non-self-regulating processes.
• Development of new IMC correlations that determine the filter time constant based on process model and desired closed-loop time constant.
• Validation through simulation studies and experiments on a bench-scale system.

Main Results:

• The proposed IMC tunings for PID with Filter controllers demonstrate effective setpoint tracking and disturbance rejection for non-self-regulating processes.
• Performance comparable to existing PID tuning correlations (filtered and unfiltered).
• Significantly reduced controller output action compared to other methods.

Conclusions:

• The developed IMC tuning correlations successfully extend the IMC framework to PID with Filter controllers for non-self-regulating processes.
• The novel approach offers improved performance and reduced control effort, completing the IMC tuning suite.
• This work provides a valuable tool for optimizing control of integrating processes using PID with Filter controllers.