自动化学报2018，Vol.44Issue(1)：74-86,13.DOI:10.16383/j.aas.2018.c160547
基于变换函数与填充函数的模糊粒子群优化算法
Fuzzy Partical Swarm Optimization Based on Filled Function and Transformation Function
摘要
Abstract
A fuzzy partical swarm optimization(PSO)based on filled function and transformation function(FPSO-TF) is proposed. Based on the multi-loop fuzzy controlsystem with different membership function the algorithm combines transformation function and filled function to reduce the chances of falling into local minima,and jumping out of a local minimum. It is fast and efficient to search for the global optimal solution. To compare the proposed algorithm with several different types of improved algorithms, a Matlab simulation is given. The result also verifies the effectiveness of the algorithm.关键词
变换函数法/填充函数法/模糊控制/粒子群算法Key words
Transformation function/filled function/fuzzy control/partical swarm optimization(PSO)引用本文复制引用
吕柏权,张静静,李占培,刘廷章..基于变换函数与填充函数的模糊粒子群优化算法[J].自动化学报,2018,44(1):74-86,13.基金项目
国家自然科学基金(61273190)资助Supported by National Natural Science Foundation of China(61273190) （61273190）
