Optimal FOPID controller design for an AVR system using a Chaotic-Enhanced Phototropic Growth Algorithm (C-PGA)

Area of Science:

• Control Systems Engineering
• Optimization Algorithms
• Electrical Engineering

Background:

• Automatic Voltage Regulator (AVR) systems require precise control for stable power supply.
• Tuning fractional-order PID (FOPID) controllers presents a high-dimensional, non-convex optimization challenge.
• Existing algorithms like Phototropic Growth Algorithm (PGA) can suffer from premature convergence.

Purpose of the Study:

• To develop an improved optimization algorithm for FOPID controller tuning in AVR systems.
• To enhance global exploration and local exploitation capabilities in optimization.
• To achieve superior voltage regulation performance with minimal overshoot and error.

Main Methods:

• Proposed a Chaotic-Enhanced Phototropic Growth Algorithm (C-PGA) by integrating a Logistic chaotic map into the standard PGA.
• Utilized a weighted multi-objective function considering Integral Time Absolute Error (ITAE), overshoot, and steady-state error.
• Conducted simulations in MATLAB/Simulink and performed Wilcoxon rank-sum tests for performance comparison.

Main Results:

• The C-PGA-tuned FOPID controller demonstrated near-zero overshoot and improved transient responses.
• Achieved satisfactory stability under significant parameter perturbations (± 50%) and effective disturbance rejection.
• Outperformed classical (PSO, GA) and modern (RIME, DBO) algorithms in comparative tests.

Conclusions:

• The C-PGA is a robust and effective optimization technique for FOPID controllers in AVR systems.
• The proposed method offers a promising solution for enhanced voltage regulation.
• Further research can explore its application in more complex system models.