Abstract: In order to improve the problem of premature and performance of optimization，a hybrid algorithm of particle swarm optimization and genetic algorithm is proposed for parameters optimization of PID controller by applying particle swarm optimization to the mutation operation of genetic algorithm.The simulation and experimental results show that the novel algorithm is superior to simple genetic algorithm，can overcome premature phenomena，reduce the influence of random initial population，and improve the convergence precision，which demonstrates the proposed method has better performance of convergence and fine ability of global optimization.

Key words: genetic algorithm, particle swarm optimization, PID controller, simulation

摘要： 为了改善单纯遗传算法早熟收敛与寻优能力不足的问题，将粒子群算法引入遗传算法变异操作中，提出了一种基于遗传算法与粒子群算法的组合算法。将改进的遗传算法应用于PID控制器参数优化中，通过仿真实验表明，新算法效果明显优于单纯遗传算法，能有效克服早熟收敛现象、降低随机性初始种群的影响、提高算法收敛精度，具有良好的收敛性和寻优能力。

关键词: 遗传算法, 粒子群算法, PID控制器, 仿真