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碳浓度偏高是导致航站楼内空气质量不佳的主要原因之一,且航站楼内随旅客数量变化碳浓度呈现的非平稳性给其控制带了挑战。为了营造航站楼内良好的空气质量,本文设计基于数据驱动的碳浓度控制系统,该系统根据航站楼内碳浓度、新风量等环境数据组成的信息向量在基础数据库中选取邻元素,通过参数调节器对邻元素的PID参数进行有向学习修正,实现系统PID参数在线优化。利用MATLAB/Simulink平台根据航站楼实际环境建立碳浓度控制系统进行应用仿真,结果表明:该系统通过参数在线优化实现了非平稳碳浓度的良好控制,可保证航站楼内碳浓度低于800ppm,系统稳态误差小于1%,与定风量系统相比节约风量约30%。该系统在为旅客提供良好的空气质量的同时可为航站楼节能设计提供参考。
The high carbon concentration is one of the major causes of poor air quality in the terminal building, and the non-stationary carbon concentration as the number of passengers in the terminal fluctuates presents challenges to its control. In order to create a good air quality in the terminal building, a data-driven carbon concentration control system is designed in this paper. The system selects the adjacent elements in the basic database based on the information vector consisting of environmental data such as carbon concentration in the terminal building and fresh air volume, The parameter adjuster carries out the directional learning correction to the PID parameters of the neighboring elements to realize the online optimization of the system PID parameters. The simulation of carbon concentration control system was established by using MATLAB / Simulink platform according to the actual environment of the terminal building. The results show that the system can achieve good control of non-stationary carbon concentration through on-line optimization of parameters, which can guarantee the carbon concentration in the terminal less than 800ppm , The system steady-state error is less than 1%, compared with the constant air volume system saves about 30% of air volume. The system provides passengers with good air quality while providing reference for energy-saving terminal design.