基于自调整因子优化的模糊控制器研究  

Research on Fuzzy Controller Based on Self-adjusting Factor Optimization

作　　者：李智敏[1,2] LI Zhi-min(Schoolo of Electrical and Electronic Engineering,Minnan University of Science and Technology,Shishi Fujian,362700;Key Laboratory of Industrial Automation Control Technology and Information Processing of Universities in Fujian,Shishi Fujian,362700)

机构地区：[1]闽南理工学院电子与电气工程学院,福建石狮362700 [2]工业自动化控制技术与信息处理福建省高校重点实验室,福建石狮362700

出　　处：《山西大同大学学报（自然科学版）》2021年第2期15-16,35,共3页Journal of Shanxi Datong University(Natural Science Edition)

基　　金：工业自动化控制技术与信息处理福建省高校重点实验室项目[闽教科〔2017〕103号];2019年福建省本科高校一般教育教学改革研究项目[FBJG20190315];2019年度辽宁省自然基金计划[2019-KF-23-07]。

摘　　要：由于模糊控制器是一种基于语言的控制器,对被控对象的数学模型要求不高,所以应用广泛,但是模糊控制存在着模糊规则一旦确定下来则无法在线调整的不足。当被控对象受到外界扰动影响时,模糊规则无法对应及时调整,导致系统的控制精度变差。因此,为了提高其控制精度,采用优化手段改进模糊控制器的不足势在必行。本文在分析各种优化手段后采用自调整因子方法对模糊控制器进行优化研究。最后,对比传统控制,通过仿真表明该方案的有效性。As a language-based controller, fuzzy controller is widely used due to its low requirements on the mathematical model of the controlled object. However, once the fuzzy rules are determined, it cannot be adjusted online. When the controlled object is affected by the external disturbance, the fuzzy rules cannot be adjusted in time, which results in the deterioration of the control precision of the system. Therefore, in order to improve its control accuracy, it is imperative to adopt optimization methods to improve the shortcomings of fuzzy controller. In this paper, after analyzing various optimization methods, the self-adjusting factor method is used to optimize the fuzzy controller. Finally, compared with the traditional control, MATLAB simulation shows the effectiveness of the scheme.

关 键 词：模糊控制器 优化 自调整因子 仿真 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]