Genetic algorithms applied in online autotuning PID parameters of a liquid-level control system

In this paper, a simple genetic algorithm (GA) method has been applied in a real-time experiment on a liquid-level control system for online autotuning proportional-integral-derivative (PID) parameters. Our proposed method can automatically choose the best PID parameters for each generation. Then, using the reproduction, crossover and mutation to create the new population for other PID parameters, it can continuously control the liquid-level system until the preset iteration number is reached. Finally, the best PID parameters can be obtained. Furthermore, two selection methods, roulette wheel and tournament, have been compared in real-time experiments. Real-time experimental results are given to demonstrate the effectiveness and usefulness for online tuning PID parameters via this evolution process.