A Novel 2-DOF PIDA control strategy with GCRA-based parameter optimization for electric furnace temperature control

Area of Science:

• Control Systems Engineering
• Industrial Automation
• Mechatronics

Background:

• Electric furnace temperature regulation faces challenges due to nonlinear dynamics, thermal inertia, and time delays.
• Conventional single-degree-of-freedom PID and PIDA controllers show performance limitations in these complex systems.
• Need for advanced control strategies to achieve accurate and energy-efficient temperature management.

Purpose of the Study:

• To propose a novel two-degree-of-freedom (2-DOF) PID-acceleration (PIDA) controller for electric furnace temperature control.
• To employ the greater cane rat algorithm (GCRA) for optimizing the 2-DOF PIDA controller parameters.
• To enhance both transient and steady-state performance using an adaptive objective function.

Main Methods:

• Development of a 2-DOF PIDA controller with independent feedforward paths for set-point tracking and disturbance rejection.
• Application of the greater cane rat algorithm (GCRA) for controller parameter tuning.
• Evaluation using simulations and comparison against metaheuristic algorithms (PFA, HOA, L-SHADE, PSO) and benchmark methods.

Main Results:

• The GCRA-based 2-DOF PIDA controller achieved superior performance, with 1.8382% overshoot and 3.4542s settling time in nominal conditions.
• Demonstrated robustness against load disturbances and measurement noise, maintaining <2.5% overshoot and <4s settling time.
• Outperformed existing state-of-the-art metaheuristic tuning methods in key performance metrics.

Conclusions:

• The proposed GCRA-based 2-DOF PIDA controller offers a high-precision and energy-efficient solution for electric furnace temperature regulation.
• The 2-DOF structure effectively addresses challenges posed by nonlinear dynamics and time delays.
• This approach represents a significant advancement for industrial temperature control systems requiring high accuracy and efficiency.