果蝇优化算法和粒子群优化算法的应用对比

The contrast of drosophila optimization and particle swarm optimization's application

参数优化一直是控制系统重要的一个环节,现在常用的优化算法有蚁群算法、遗传算法、粒子群优化算法。然而现在这些算法普遍存在鲁棒性差、陷入局部最优等缺点。果蝇优化算法作为一种较新的群体优化算法与粒子群有颇多的相似之处。本文以水轮机组调速系统PI控制参数为优化对象,分别以粒子群优化算法和果蝇优化算法进行参数优化,通过分析二者的优化过程与结果,对比了两种优化算法的优缺点,证明了果蝇优化算法的可行性。

TParameter optimization has been an important aspect of the control system,optimization algorithm includs the composition of the ant colony algorithm, genetic algorithm, particle swarm optimization algorithm.Now, however, the prevalence of these algorithms robustness local optimum drawback.This paper presents a latest optimization algorithm - Drosophila optimization algorithm.Hydraulic turbine speed control system is optimizated, by particle swarm optimization and the Drosophila optimization algorithm parameter optimization.Finally, in simulink dynamic simulation, comparing the results of the optimizations.