计算机科学与探索2024，Vol.18Issue(8)：2065-2079,15.DOI:10.3778/j.issn.1673-9418.2305101
动态拓扑结构混合粒子群算法及其应用
Hybrid Particle Swarm Algorithm with Dynamic Topology and Its Applications
摘要
Abstract
The traditional particle swarm optimization algorithm is slow to find the optimal solution and easy to fall into the local optimal solution when facing the parameter tuning problem of higher dimensions.This paper proposes a dynamic ring topolopy hybrid firefly and particle swarm optimization(DynRing-hfpso)algorithm.This algorithm takes the particle swarm algorithm as the base,incorporates advantages of firefly algorithm,enables the particles to alternate between global search and local exploration independently in the iterative process by defining the selection logic,and improves the utilization of information in the iterative process of the algorithm with an adaptive particle velocity and position constraint method.In addition,the particle swarm topology is improved to enhance the search space coverage and equalize the convergence speed with dynamic multi-neighborhood ring topology.Dynamic performance analysis and ablation experiments are set up to verify the effectiveness of the particle distribution quality and improvement measures in the algorithm.Then,a velocity servo system under fractional order proportion integra-tion differentiation(FOPIλDμ)control is used as an application scenario to compare the performance of this algo-rithm with the other four algorithms.The results show that the DynRing-hfpso algorithm has faster convergence speed and better convergence accuracy than the existing metaheuristic optimization algorithms,and shows stronger robustness in several experiments.关键词
环形拓扑结构/粒子群算法/萤火虫算法/分数阶PID/自整定Key words
ring topology/particle swarm optimization/firefly algorithm/fractional order PID(proportion integra-tion differentiation)/self-tuning分类
信息技术与安全科学引用本文复制引用
王浩丞,李凌..动态拓扑结构混合粒子群算法及其应用[J].计算机科学与探索,2024,18(8):2065-2079,15.基金项目
国家重点研发计划(2020YFC2003802) （2020YFC2003802）
苏州市科技计划(SYC2022109). This work was supported by the National Key Research and Development Program of China(2020YFC2003802),and the Science and Technology Plan of Suzhou(SYC2022109). （SYC2022109）
