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

作　　者：吕柏权[1] 张静静[1] 李占培[1] 刘廷章[1] 

机构地区：[1]上海大学机电工程与自动化学院,上海200072

出　　处：《自动化学报》2018年第1期74-86,共13页Acta Automatica Sinica

基　　金：国家自然科学基金(61273190)资助~~

摘　　要：本文提出了一种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,FPSO-TF).以基于不同隶属度函数的多回路模糊控制系统为基础,进一步结合变换函数与填充函数,使该算法减少了陷入局部最优的可能,又可以跳出局部极小值点至更小的点,快速高效地搜索到全局最优解.最后采用基准函数对此算法进行测试,并与几种不同类型的改进算法进行对比分析,验证了此算法的有效性与优越性.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 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]