【摘要】 针对现有控制方式仅以车内温度为控制对象所存在的弊端,建议以整个车内环境为控制对象,以反映热环境舒适性和车内空气品质的宏观、微观控制指标为依据,将模糊技术和神经网络技术相结合,建立实时控制系统。系统模型分为输入层、计算层和控制层,分别由传感器和主控计算机实现数据实时检测、计算和控制功能,并采用自适应神经模糊推理系统(ANFIS)用于铁路客车中的空调处理过程控制,以实现铁路客车空调实时控制,从而较为全面、有效地改善空调客车车内环境品质。更多还原

【Abstract】 In consideration of the problems existing in the present control method which only takes the indoor temperature as the the control object, the paper proposes to take the complete indoor environment as the control object and to base on the macro and micro control index of the thermal environment comforts and indoor air quality, combines the fuzzy technique and the neural network, and sets up a realtime control system. The system model breaks down into three layers: the inputting layer, calculation layer, control layer, respectively controlled by the sensors and the main computer to realize the data realtime measure, calcuation and control. The ANFIS is used to control the air conditioning work process in the railway passenger car so as to realize realtime control of the airconditioning in the railway passenger cars. As a result the indoor environment quality inside the train is effectively and comprehensively enhanced.更多还原