An optimal design for an automatic voltage regulation system using a multivariable PID controller based on hybrid...

Area of Science:

• Electrical Engineering
• Control Systems
• Optimization Algorithms

Background:

• Automatic Voltage Regulator (AVR) systems require precise parameter tuning for stability and performance.
• Traditional tuning methods may struggle with complex controller types like fractional-order PID (FOPID) controllers.
• Metaheuristic algorithms offer potential for optimizing complex control systems.

Purpose of the Study:

• To develop a novel hybrid metaheuristic algorithm, SA-WSO, for tuning AVR system controller parameters.
• To evaluate the performance of SA-WSO in optimizing various PID and FOPID controllers, including a novel filtered FOPID.
• To demonstrate the superiority of the SA-WSO algorithm in terms of convergence speed and controller performance.

Main Methods:

• Development of a hybrid simulated annealing (SA) and white shark optimization (WSO) algorithm (SA-WSO).
• Application of SA-WSO to tune parameters of three types of controllers: PID, FOPID, and a novel filtered FOPID.
• Simulation and comparative analysis of controller performance in an AVR system under various conditions.

Main Results:

• The SA-WSO algorithm successfully optimized the parameters for all tested controllers, including the filtered FOPID.
• SA-WSO demonstrated superior performance compared to existing methods, particularly in disturbance rejection and robustness.
• The hybrid algorithm exhibited significantly improved convergence speed.

Conclusions:

• The proposed SA-WSO algorithm is highly effective for tuning PID and FOPID controllers in AVR systems.
• The SA-WSO algorithm offers significant advantages, including enhanced convergence speed and robust performance.
• This hybrid approach provides a powerful tool for optimizing complex control systems.