摘要
针对遗传算法的特点 ,提出一种用模糊控制的方法来调整交叉概率和变异概率的改进模糊遗传算法及其算法结构 ,并将其应用于神经模糊控制器的综合优化设计。在以二阶模型为控制对象的仿真结果表明 ,此种模糊遗传算法不仅加快了解的收敛速度 。
Based on the characteristics of genetic algorithm, an improved fuzzy genetic algorithm (FGA) and its algorithm structure are proposed, in which the crossover probability and mutation probability are adjusted by fuzzy control method. Then FGA is used into the integrated optimal design of neuro-fuzzy controller. The results of simulation on the second order control model show that this kind of FGA can improve both the convergent speed and the quality of the solution.
出处
《计算机仿真》
CSCD
2004年第6期122-126,共5页
Computer Simulation
基金
国家 8 63项目 (编号 :2 0 0 2AA5 170 2 0 )
关键词
模糊遗传算法
神经模糊控制器
交叉概率
变异概率
Fuzzy genetic algorithm
Neuro-fuzzy control
Crossover probability
Mutation probability
