基于神经网络补偿的温湿度试验箱模糊解耦控制
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摘要
该文分析温湿度试验箱内部的温湿度耦合关系,提出采用模糊控制方法作为温湿度试验箱温度和湿度的控制方法,并采用模糊补偿方法和神经网络补偿方法对温湿度试验箱内部的温湿度耦合关系进行补偿。结果表明,该文所提出的方法可以对温湿度试验箱的温湿度进行解耦控制,使控制精度大大提高。
In this paper,the temperature and humidity coupling relationship between the temperature and humidity chamber is analyzed,and the fuzzy control method is used as the control method of the temperature and humidity of the temperature and humidity chamber. The fuzzy compensation method and the neural network compensation method are used to control the temperature and humidity. The temperature and humidity coupling relationship to compensate. The results show that the proposed method can decouple the temperature and humidity of the temperature and humidity chamber to improve the control precision.
In this paper,the temperature and humidity coupling relationship between the temperature and humidity chamber is analyzed,and the fuzzy control method is used as the control method of the temperature and humidity of the temperature and humidity chamber. The fuzzy compensation method and the neural network compensation method are used to control the temperature and humidity. The temperature and humidity coupling relationship to compensate. The results show that the proposed method can decouple the temperature and humidity of the temperature and humidity chamber to improve the control precision.
引文
[1]千红涛.环境试验箱的可适应产品平台设计方法与应用研究[D].徐州:中国矿业大学,2015.
[2]王洪航,褚建新,张江明,等.基于模糊控制的温湿度试验系统的研究[J].化工自动化及仪表,2015,42(03):300-302.
[3]申中鸿,杨林,刘群兴,等.高低温试验箱温湿度控制技术研究[J].伺服控制,2013(10):55-57.
[4]王瑾,袁战军,李小斌.智能温度控制系统的设计[J].自动化与仪器仪表,2016(08):175-177.
[5]张玲,张文苑,郑恩让.一种模糊解耦控制系统的设计与仿真研究[J].计算机仿真,2010,27(08):118-121.
[6] RAN Maopeng,WANG Qing,HOU Delong,et al. Backste-pping design of missile guidance and control based on adaptive fuzzy sliding mode control[J]. Chinese Journal of Aeronautics,2014,27(03):634-642.
[7] Direct adaptive neural control for stabilization of nonlinear time-delay systems[J]. Science China(Information Sciences),2010,53(04):800-812.
[8]陈文科,唐黄正.一种蒸汽养护窑温湿度模糊解耦控制系统仿真研究[J].科技创新与应用,2017(36):12-13.
[9]孙碧.模糊自适应控制在温湿度系统中的应用与研究[D].广州:华南理工大学,2015.
[10]彭基伟,吕文华,行鸿彦,等.基于改进GA-BP神经网络的湿度传感器的温度补偿[J].仪器仪表学报,2013,34(01):153-160.
[11]张宁子,杨泽林,俞晓红.基于模糊PID温湿度解耦控制器的仿真与结果分析[J].宁夏工程技术,2013,12(01):14-17.
[12]赵静.精馏塔温度模糊解耦控制系统的研究[J].工业仪表与自动化装置,2013(06):50-54.
[13]刘珑龙,刘雪锋,周西龙.基于模糊神经网络的多变量系统的解耦方法[J].中国海洋大学学报(自然科学版),2013,43(02):99-104.
[14] Zhisheng NI,Mingyan WANG. Research on the Fuzzy Neural Network PID Control of Load Simulator Based on Friction Torque Compensation[C]. Intelligent HumanMachine Systems and Cybernetics(IHMSC),2014 Sixth International Conference on,2014.
[15] Wei ZHANG,Hong MA,Simon X YANG. A neurofuzzy decoupling approach for real-time drying room control in meat manufacturing[J]. Expert Systems With Applications,2015,42(3):1039-1049.
[2]王洪航,褚建新,张江明,等.基于模糊控制的温湿度试验系统的研究[J].化工自动化及仪表,2015,42(03):300-302.
[3]申中鸿,杨林,刘群兴,等.高低温试验箱温湿度控制技术研究[J].伺服控制,2013(10):55-57.
[4]王瑾,袁战军,李小斌.智能温度控制系统的设计[J].自动化与仪器仪表,2016(08):175-177.
[5]张玲,张文苑,郑恩让.一种模糊解耦控制系统的设计与仿真研究[J].计算机仿真,2010,27(08):118-121.
[6] RAN Maopeng,WANG Qing,HOU Delong,et al. Backste-pping design of missile guidance and control based on adaptive fuzzy sliding mode control[J]. Chinese Journal of Aeronautics,2014,27(03):634-642.
[7] Direct adaptive neural control for stabilization of nonlinear time-delay systems[J]. Science China(Information Sciences),2010,53(04):800-812.
[8]陈文科,唐黄正.一种蒸汽养护窑温湿度模糊解耦控制系统仿真研究[J].科技创新与应用,2017(36):12-13.
[9]孙碧.模糊自适应控制在温湿度系统中的应用与研究[D].广州:华南理工大学,2015.
[10]彭基伟,吕文华,行鸿彦,等.基于改进GA-BP神经网络的湿度传感器的温度补偿[J].仪器仪表学报,2013,34(01):153-160.
[11]张宁子,杨泽林,俞晓红.基于模糊PID温湿度解耦控制器的仿真与结果分析[J].宁夏工程技术,2013,12(01):14-17.
[12]赵静.精馏塔温度模糊解耦控制系统的研究[J].工业仪表与自动化装置,2013(06):50-54.
[13]刘珑龙,刘雪锋,周西龙.基于模糊神经网络的多变量系统的解耦方法[J].中国海洋大学学报(自然科学版),2013,43(02):99-104.
[14] Zhisheng NI,Mingyan WANG. Research on the Fuzzy Neural Network PID Control of Load Simulator Based on Friction Torque Compensation[C]. Intelligent HumanMachine Systems and Cybernetics(IHMSC),2014 Sixth International Conference on,2014.
[15] Wei ZHANG,Hong MA,Simon X YANG. A neurofuzzy decoupling approach for real-time drying room control in meat manufacturing[J]. Expert Systems With Applications,2015,42(3):1039-1049.