Fast Genetic Algorithms Used for PID Parameter Optimization

PID parameter optimization is an important problem in control field. This paper presents a kind of fast genetic algorithms, which have a lot of improvements about population, selection, crossover and mutation in comparison with simple genetic algorithms. These fast genetic algorithms are used in PID parameter optimization for common objective model to remedy flaws of simple genetic algorithms and accelerate the convergence. The algorithms are simulated with MATLAB programming. The simulation result shows that the PID controller with fast genetic algorithms has a fast convergence rate and a better dynamic performance.