A simple nonlinear PD controller for integrating processes.

Area of Science:

• Control Engineering
• Industrial Process Control
• Nonlinear Control Systems

Background:

• Integrating processes often exhibit poor control performance with standard PID tuning.
• Traditional PID controllers struggle with overshoot and settling time in integrating systems.
• Internal Model Control (IMC) offers improvements but limited benefits for disturbance rejection.

Purpose of the Study:

• To propose a novel auto-tuning proportional-derivative (APD) controller for improved industrial process control.
• To enhance controller performance during set point changes and load disturbances.
• To address limitations of existing PID and PD tuning rules for integrating plus delay processes.

Main Methods:

• Developed an auto-tuning PD controller (APD) with a nonlinear gain updating factor (α).
• Utilized instantaneous normalized error (eN) and change of error (ΔeN) to determine α.
• Tested APD performance against established PD and PID tuning rules.

Main Results:

• The proposed APD controller demonstrated superior performance compared to conventional tuning methods.
• Significant reductions in overshoot and settling time were observed.
• Effective disturbance rejection capabilities were validated on integrating plus delay (IPD) and first-order integrating plus delay (FOIPD) processes.

Conclusions:

• The APD controller offers a robust and effective solution for controlling integrating processes.
• The nonlinear gain adjustment strategy provides enhanced dynamic response and disturbance handling.
• Experimental validation on a servo position control system confirms the practical applicability of the proposed APD scheme.