细菌群觅食优化算法及PID参数优化应用

Bacterial Swarm Foraging Optimization Algorithm and Its Application in Optimization of PID Parameters

针对细菌觅食(BF)算法收敛速度慢和粒子群优化(PSO)算法早熟的缺点,提出了一种细菌群觅食优化(BSFO)算法。将PSO算法中粒子速度的更新公式替代BF算法位置公式中的方向向量,使细菌在优化过程中具备感应周围细菌位置并向细菌群体历史最优位置游动的能力。Benchmark函数的测试表明,BSFO算法对于大部分测试函数的结果较为理想。将BSFO算法用于材料试验机电液位置伺服系统的PID控制器参数寻优仿真,获得了较好的控制性能。

To overcome the shortages of slow convergence in bacterial aigorltnin auu premature in particle swarm optimization（PSO） algorithm, a bacterial swarm foraging optimization （BSFO） algorithm was proposed. The velocity updating formula in PSO was used to replace the direc tion vector of position formula in BF algorithm, therefore each bacterium had the ability of perceiving the position of the neighborhood bacteria and moving to the historical best position of the whole swarm. The optimal results of benchmark test functions show that the BSFO algorithm has better performance for most of the functions. Besides, the BSFO algorithm was applied to the simulation of optimization of the PID controller＇s parameters, which was used in an electrohydraulic position ser vo system of material testing machine, and the PID control system has good control performance.