基于ANFIS-IGA的Fuzzy-PID系统对切削用量的控制研究  

Study on Control of Cutting Parameters Based on ANFIS-IGA of Fuzzy-PID System

作　　者：魏建安 黄海松[1] 康佩栋 WEI Jian-an;HUANG Hai-song;KANG Pei-dong(Key Laboratory of advanced Manuthcturing Technology,Ministry of Education,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学现代制造技术教育部重点实验室,贵阳550025

出　　处：《组合机床与自动化加工技术》2018年第8期118-123,共6页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：贵州工业攻关重点项目(黔科合GZ字[2015]3009);贵州省自然科学基金(黔科合J字[2015]2043);贵州大学研究生创新基金项目(研理工2017037)

摘　　要：针对传统Fuzzy-PID控制系统控制精度不高,响应速度较差,以及应用专家整定法需要大量经验等缺点,文章选取切削用量作为控制对象,提出了基于ANFIS-IGA的改进算法,设计了基于该改进算法的CJK6132A经济型数控机床切削用量控制系统,以达到对切削用量的精良控制。MATLAB仿真表明:与传统Fuzzy-PID系统相比,该系统不但具有更好的动态特性,而且具有更好的控制精度与鲁棒性,同时又节省了专家整定法中收集数据的时间。Aiming at the shortcomings of traditional Fuzzy-PID control system,such as the control precision is not ideal,the response speed is relatively poor and the expert setting method needs a lot of experience,the cutting amount was chooesd as the control object and propised an improved algorithm based on ANFIS-IGA（ adaptive network based fuzzy inference system-improved genetic algorithm） in the paper. At the same time,basing on the improved algorithm,a CJK6132 A economical CNC machine tool cutting amount control system was designed to achieve excellent control of the amount of cutting. The MATLAB simulation results showthat the proposed system not only can achieve better dynamic performance than the traditional Fuzzy-PID system,but also has better control precision and robustness,and simultaneously saves the time of collecting data in the expert tuning method.

关 键 词：自适应神经网络模糊推理系统 遗传算法 模糊PID控制优化 MATLAB仿真 

分 类 号：TH166[机械工程—机械制造及自动化] TG506[金属学及工艺—金属切削加工及机床]