基于智能控制算法的中央空调变风量控制系统研究

发布时间：2018-01-21 04:07

本文关键词： 变风量中央空调末端控制器 LabVIEW 模糊神经网络　出处：《吉林建筑大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着世界对全球变暖问题的重视,节能成为了近年来的被重点关注的问题。建筑物能耗一直在国家能耗里占有重要比重,而其中空调系统占用的比重是建筑物能耗里最大的,所以如何降低空调系统的能耗是近年来众多研究学者研究的课题,无论是独立式空调还是中央空调都出现了大量的新思路用于降低空调的能耗,本文关注的内容就是其中对降低变风量中央空调能耗的问题。传统的变风量中央空调主要使用PID作为末端控制器的控制算法,在面对复杂或者多变的环境时,不能很好的适应。为了解决这个问题,近年来模糊控制方法被应用在了变风量空调系统的末端控制器上,经过了理论研究阶段后应用的越来越普及,但是模糊控制往往很依赖模糊规则与专家经验,不具备自我学习适应能力。本文从变风量中央空调系统中的末端控制装置入手,在分析了变风量中央空调的系统特性后,探索研究用模糊控制技术和神经网络技术实现变风量中央空调系统的末端控制器。根据模糊控制技术与神经网络技术的特点,结合成为模糊神经网络,它以实际温度与设定温度的温度差、温度变化速率作为模糊控制的输入,通过神经网络的自学习能力不断的修正语言值论域和对应的隶属度函数,完善模糊控制算法的输出结果,进而提升变风量中央空调末端控制器的智能化程度。本文依据现有的变风量中央空调系统,实现了使用模糊神经网络的末端控制器,并对其进行了测试。测试的结果表明在抗干扰能力、过渡时间以及降低能耗上,该末端控制器都优于使用PID作为控制算法的末端控制器,验证了模糊神经网络在变风量中央空调末端控制上的有效性。
[Abstract]:With the attention of the world to the problem of global warming, energy conservation has become the focus of attention in recent years. Building energy consumption has been an important proportion in the national energy consumption. Among them, the proportion of air conditioning system occupied is the largest in building energy consumption, so how to reduce the energy consumption of air conditioning system has been studied by many researchers in recent years. There are a large number of new ideas to reduce the energy consumption of air conditioning, whether independent air conditioning or central air conditioning. This paper focuses on the problem of reducing the energy consumption of VAV central air-conditioning. The traditional VAV central air conditioning mainly uses PID as the control algorithm of the terminal controller. In the face of complex or changeable environment, it can not adapt well. In order to solve this problem, fuzzy control method has been applied to the terminal controller of VAV air conditioning system in recent years. After the stage of theoretical research, the application of fuzzy control is becoming more and more popular, but fuzzy control often depends on fuzzy rules and expert experience. This paper starts with the terminal control device in VAV central air conditioning system and analyzes the characteristics of VAV central air conditioning system. The end controller of VAV central air conditioning system is realized by using fuzzy control technology and neural network technology. According to the characteristics of fuzzy control technology and neural network technology, the fuzzy neural network is combined into a fuzzy neural network. It takes the temperature difference between the actual temperature and the set temperature, the temperature change rate as the input of fuzzy control, and constantly modifies the linguistic value field and the corresponding membership function through the self-learning ability of the neural network. Improve the output of fuzzy control algorithm, and then improve the intelligent level of VAV central air conditioning terminal controller. This paper based on the existing VAV central air conditioning system. The end controller using fuzzy neural network is realized and tested. The test results show that the anti-jamming ability, transition time and energy consumption are reduced. The end controller is superior to the terminal controller using PID as the control algorithm. The effectiveness of the fuzzy neural network in the terminal control of VAV central air conditioning system is verified.
【学位授予单位】：吉林建筑大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273;TU831

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