A Novel Gudermannian Function-Driven Controller Architecture Optimized by Starfish Optimizer for Superior Transient...

Area of Science:

• Electrical Engineering
• Control Systems

Background:

• Automatic Voltage Regulator (AVR) systems are crucial for maintaining stable power grids.
• Traditional PID controllers struggle with highly dynamic conditions and large signal variations.

Purpose of the Study:

• To develop an enhanced PID controller using the Gudermannian function for improved AVR transient performance.
• To optimize the controller parameters using the Starfish Optimization Algorithm (SFOA).

Main Methods:

• The Gudermannian function was integrated into a PID controller structure (G-PID).
• The Starfish Optimization Algorithm (SFOA) was employed for optimal parameter tuning.
• Simulations were conducted to evaluate transient performance under dynamic conditions.

Main Results:

• The SFOA-optimized G-PID controller achieved a fast rise time (0.0551 s) with zero overshoot and a quick settling time (0.0830 s).
• The proposed controller demonstrated superior performance compared to various optimization algorithms and advanced control schemes.
• The G-PID controller showed enhanced adaptability to large signal variations and effective overshoot suppression.

Conclusions:

• The proposed SFOA-optimized G-PID controller offers a computationally efficient and structurally simple solution for high-performance voltage regulation.
• This approach significantly enhances the transient response of AVR systems in modern power grids.
• The Gudermannian function integration provides a robust method for improving controller adaptability and stability.