PID controller tuning for an AVR system using Particle Swarm Optimisation Techniques and Genetic Algorithm Techniques; A comparison based approach

This paper presents the tuning of a Proportional-Integral-Derivative (PID) controller for an Automatic Voltage Regulator (AVR) system using a metaheuristic optimization technique. The aim is to enhance the system's dynamic response by minimizing overshoot, settling time, and steady-state error. Particle Swarm Optimization (PSO), a robust and widely applied metaheuristic technique, was selected due to its simplicity and efficiency in exploring the search space for optimal solutions. The AVR system was modelled and simulated using MATLAB and the performance of the optimized PID controller was analyzed and compared with a traditional manually tuned PID controller. The results show a significant improvement in system performance with the PSO-tuned PID controller, validating the potential of metaheuristic optimization for PID tuning in control systems.