【作者】 王丽丽； 张涛；

【Author】 Wang Lili 1 , Zhang Tao 1 1. College of Automation Electronic Engineering, Qingdao University of Sciences and Technology, Qingdao 266042

【机构】 青岛科技大学自动化与电子工程学院；

【摘要】 太阳能-相变蓄热新风系统是把太阳能技术和相变蓄热技术相结合用于房间有组织通风换气的一种新型辅助供暖系统。针对太阳能一相变蓄热新风系统的数学模型难以精确建立的特点,本文设计了基于白适应神经模糊推理的控制器。它应用BP神经元网络的误差反传算法,对新风系统的输入变量的隶属度函数和输出变量进行参数辨识。仿真结果表明:该算法采用神经网络与模糊推理结合的建模和参数辨识方法,可以很大程度上逼近太阳能一相变蓄热新风系统的特性,误差几乎为零。从而提出了一种太阳能一相变蓄热新风温度的控制方法,为更好的实现新风系统的节能减排提供了另外一种思路。更多还原

【Abstract】 A fresh air system with solar energy and phase-change thermal storage is introduced in this paper. It can not only supply fresh air to the room, but also supply parts of the heat to the room as a type of auxiliary heating to some extent. For the mathematical model of the fresh air system was difficult to accurately establish, an AFNNC (adaptive neuro-fuzzy inference system controller) was presented. It was used for parameter identification of input variables membership function and output variables applying for BP neural network back-propagation algorithm. Experimental results show that: The algorithm combining neural networks and fuzzy inference modeling and parameter identification methods can largely close to the practical data that solar energy - phase change thermal storage characteristics of the fresh air system, the error is almost zero. It finally proposed a new control method for the fresh air system which provides another idea for better energy saving.更多还原