基于粒子群优化的细菌觅食优化算法

Bacteria Foraging Optimization Algorithm Based on Particle Swarm Optimization

细菌觅食优化算法(BFOA)具有全局搜索能力强的优点,但存在收敛速度慢的缺陷。为了解决以上问题,结合收敛速度快的粒子群优化算法,提出一种基于粒子群优化的细菌觅食优化算法(BF-PSO),该改进的优化算法具有可操作性和优越性。选用测试函数和对PID控制参数整定的实例进行Matlab仿真,结果进一步显示了BF-PSO的优化能力优于BFOA,收敛速度快,且具有较好的鲁棒性。

Traditional bacterial foraging optimization algorithm has a strong global searching ability, but it has the drawback of slow con- vergence. A new bacterial foraging optimization algorithm based on particle swarm optimization （BF-PSO） is proposed to overcome the slow convergence problem of the traditional method by taking advantage of the particle swarm optimization. The proposed method is ex- pected to have good operability and advantages. Simulation experiments are carried out on Matlab with test functions and an example of PID controller tuning. The results show that BF-PSO is better than BFOA on the optimization caPabilities, convergence speed and ro- bustness.