Simulation Program for PID Tuning Based on Binary-Encoded Genetic Algorithm

This simulation program implements PID controller tuning using a binary-encoded genetic algorithm. The system employs genetic operators including selection, crossover, and mutation to evolve population chromosomes representing PID parameters (Kp, Ki, Kd). Through iterative optimization cycles, the program converges toward optimal PID values that minimize system error metrics. The binary encoding scheme allows efficient parameter space exploration while maintaining precision through bit-string resolution. Users can define system constraints and performance objectives (e.g., settling time, overshoot limits) as fitness functions for the evolutionary algorithm. The automated tuning process significantly simplifies PID optimization by replacing manual adjustments with systematic population-based search, resulting in improved control system stability and dynamic response characteristics. The simulation includes visualizations of convergence progress and performance comparisons between initial and optimized PID configurations.