摘要
针对目前带钢厚度控制精度低,不能满足生产要求的问题,将模糊神经网络与仿人智能控制有机结合,设计了一种基于模糊神经网络参数整定的热轧带钢厚度仿人智能控制策略,利用模糊神经网络对仿人智能控制器的参数进行了整定。Matlab仿真结果表明:基于模糊神经网络参数整定的仿人智能控制优于PID控制,为解决复杂工业过程的控制提供了一种新的、有效的方法。
Aiming at problem of low control precision and cannot meet requirement of production of strip thickness,combines fuzzy neural network with human-simulated intelligent control technology, design humansimulated intelligent control strategy of hot roiled strip steel thickness based on fuzzy neural network parameters setting, correct human-simulated intelligent controller parameters using fuzzy neural network. The simulation experiment result by Matlab shows that the human-simulated intelligent control method which based on fuzzy neural network has a better performance compared with PID control,it can provide a new effective method for the control of complex industrial process.
出处
《传感器与微系统》
CSCD
北大核心
2013年第10期30-33,共4页
Transducer and Microsystem Technologies
基金
山西省自然科学基金资助项目(2010011022-3)
关键词
仿人智能控制
模糊神经网络
参数整定
热轧带钢厚度控制
human-simulated intelligent control
fuzzy neural network
parameters correcting
hot-rolling strip thickness control
