Design and optimal tuning of fractional order PID controller for paper machine headbox using jellyfish search...

Area of Science:

• Control Systems Engineering
• Industrial Automation
• Optimization Algorithms

Background:

• Paper machine headbox control is critical for product quality.
• Conventional PI and PID controllers have limitations in complex systems.
• Optimizing controller parameters is essential for enhanced performance.

Purpose of the Study:

• To propose and evaluate a Jellyfish Search Optimization (JSO) algorithm for tuning Fractional Order Proportional-Integral-Derivative (FOPID) controllers.
• To enhance the efficiency and effectiveness of headbox pressure and stock level control.
• To demonstrate the superiority of the JSO-tuned FOPID controller over existing methods.

Main Methods:

• Utilized the Jellyfish Search Optimization (JSO) algorithm to tune FOPID controller parameters.
• Minimized error indices including Integral of Squared Error (ISE), Integral of Time Absolute Error (ITAE), and Integral of Absolute Error (IAE).
• Conducted simulations on the MATLAB/Simulink platform for performance evaluation.

Main Results:

• The JSO-tuned FOPID controller showed a 25% reduction in rise time, 30% improvement in settling time, and 20% decrease in overshoot compared to PID.
• JSO demonstrated higher accuracy and stability than MFO, ALO, and EHO in diverse conditions.
• Achieved superior performance in headbox pressure and stock level control.

Conclusions:

• The JSO-tuned FOPID controller is a robust and effective solution for paper machine headbox systems.
• This method offers enhanced process efficiency and control precision in industrial applications.
• JSO provides a reliable approach for optimizing complex control systems.