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An expert system for the humidity and temperature control in HVAC systems using ANFIS and optimization with Fuzzy Modeling Approach

机译:基于ANFIS的HVAC系统湿度和温度控制专家系统及其模糊建模方法的优化。

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The aim of this study is to design a HVAC system which damper gap rates have been controlled by PID controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the required humidity for the same indoor volume. The realized system has a zone with variable flow-rate by considering the ambient temperature and humidity. In the authors' previous theoretical work, PID parameters were theoretically obtained by using fuzzy sets for the same HVAC system. Optimization with Fuzzy Modeling Approach of PID parameters has been performed to maximize the performance of the system. The obtained PID parameters in the previous theoretical work were used in this study. Besides, the damper gap rates of a HVAC system with only one zone were predicted by using Artificial Neural Fuzzy Interface System (ANFIS) method. The input-output data sets of this system were first stored and then these data sets were used to obtain its intelligent model and control based on ANFIS. Efficiency of the developed ANFIS method was tested and a mean 99.98% recognition success was obtained. This paper shows that the values predicted with the ANFIS can be used to predict damper gap rate of HVAC system quite accurately. Therefore, faster and simpler solutions can be obtained based on ANFIS.
机译:这项研究的目的是设计一种暖通空调系统,该系统的风门间隙率已由PID控制器控制。其中一个风门通过使用所需室内体积所需的温度进行控制,而另一个风门通过使用对于相同室内体积所需的湿度进行控制。考虑到环境温度和湿度,所实现的系统具有流量可变的区域。在作者先前的理论工作中,理论上,对于同一HVAC系统,通过使用模糊集获得PID参数。使用PID参数的模糊建模方法进行了优化,以使系统性能最大化。在这项研究中使用了以前的理论工作中获得的PID参数。此外,采用人工神经模糊接口系统(ANFIS)方法预测了只有一个区域的HVAC系统的阻尼间隙率。首先存储该系统的输入输出数据集,然后使用这些数据集获取其基于ANFIS的智能模型和控制。测试了开发的ANFIS方法的效率,平均识别成功率为99.98%。本文表明,利用ANFIS预测的值可以非常准确地预测HVAC系统的阻尼器间隙率。因此,可以基于ANFIS获得更快,更简单的解决方案。

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