摘要
模糊控制中的模糊推理规则和隶属函数的选取往往依据相关专家或技术人员的实际经验,具有较大的人为主观性,尤其在面对具有较强的非线性系统和未知动态环境条件下,其控制性能达不到客观要求。本文采用改进的遗传算法优化模糊控制中的比例因子,从而对控制规则和隶属函数进行优化。仿真结果表明,经过优化后的模糊控制器和传统的Fuzzy-PID控制器相比,其控制规则和隶属函数更加客观合理,控制系统的动、静态性能都有较大提高。
Nowadays,many fuzzy PID controllers are largely used in industrial control dom-ain ,but me inferential rules of fuzzy PID controllers take on more subjective experience of the experts, so it could not adapted to the control unit under some eases ,especially with the great disturbance and more unknown conditions .This paper presented an approach to optimize the sealing factors of fuzzy PID controller using improved Genetic Algorithm （GA）,tbe scaling factors would regulate the output of the controller in terms of the objective function, thereby to improve the rules and membership functions. The simulated experiment demonstrates the effectiveness and feasibility of the optimal controller.
出处
《微计算机信息》
北大核心
2006年第10S期20-22,共3页
Control & Automation
基金
上海市科委发展基金(015115042)
关键词
模糊控制
遗传算
PID控制
比例因子
Fuzzy Control,Genetic Algorithms, PID control,Scaling factor
