基于模糊控制的遗传算法优化研究  

Research of Genetic Algorithm Based on Fuzzy Control

作　　者：李雅琼[1] LI Yaqiong(Fuyang Vocational and Technical College, Fuyang Anhui 236000, Chin)

机构地区：[1]阜阳职业技术学院,安徽阜阳236000

出　　处：《长沙大学学报》2016年第5期58-61,共4页Journal of Changsha University

基　　金：阜阳职业技术学院校级科研项目(批准号:2014KYXM07);省级质量工程机电一体化技术教学团队项目(批准号:2014jxtd058)

摘　　要：模糊控制方法简单,特别适合不宜建模或动态特性不易掌握的系统.但模糊控制易受人的经验的影响,且不具有学习能力,有时很难达到预计的控制效果.而遗传算法具有遗传特性,与模糊控制结合后能给其带来学习能力,且遗传算法本身能进行全局搜索,一般不会陷入局部最优运算,理论上两者结合后可以达到更好的控制效果.以倒立摆模型为例,matlab仿真结果证明了两者结合的可行性,且结合后能更快地得到最优解.Fuzzy control is a simple intelligent control method. This method is especially suitable for the system that is difficult to be modeled or to be mastered in dynamic characteristics. However,fuzzy control is easily influenced by people＇s experience,and does not have the ability to learn,so sometimes it is hard to reach the expected control effect. On the contrary,genetic algorithm which can perform a global research and will not get into local optimal operation has the hereditary capacity. So,genetic algorithm can bring fuzzy control learning ability and better control effect. Based on the model of inverted pendulum,the matlab simulation results prove the feasibility of the combination between fuzzy control and genetic algorithm. The combination of fuzzy and genetic algorithm can get the optimal solution more quickly.

关 键 词：模糊控制 遗传算法 MATLAB仿真 倒立摆 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP273[自动化与计算机技术—控制科学与工程]