PID Control Tuned with BG-PSO Algorithm

This article presents a comprehensive explanation of PID control tuned using the BG-PSO algorithm for reference purposes. We introduce the fundamental principles and applications of the BG-PSO algorithm, which employs binary grid partitioning and particle swarm optimization for efficient parameter space exploration. The implementation methodology demonstrates how to utilize this algorithm for precise PID controller tuning through systematic parameter optimization. The approach includes initialization of particle positions representing PID gains (Kp, Ki, Kd), fitness evaluation using performance indices like ISE or IAE, and iterative updating of particle velocities and positions through cognitive and social components. Additionally, we provide practical case studies and sample MATLAB/Python code snippets featuring key functions such as population initialization, fitness calculation, and convergence criteria implementation. These resources aim to help learners better understand and apply this control method effectively, with particular emphasis on parameter tuning strategies and optimization performance analysis.