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An adaptive artificial neural network-based supply air temperature controller for air handling unit

机译:基于自适应神经网络的送风温度控制器

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摘要

In this paper, an adaptive neural network (NN)-based supply air temperature controller is proposed for an air handling unit (AHU) in heating, ventilation and air conditioning (HVAC) systems. The heat exchange dynamics within an AHU is complicated and almost impossible to model exactly. Moreover, it is subject to multiple external disturbance variables. To accommodate such uncertainties, a direct adaptive controller based on a two-layer NN is introduced to maintain the desired supply air temperature under varying operating conditions. To verify the performance of the proposed scheme, extensive experiments have been conducted on a pilot HVAC system. The experimental results substantiate that our method outperforms a conventional proportional-integral-derivative controller in terms of promptness to changing working conditions and robustness to external disturbances.
机译:本文针对供暖,通风和空调(HVAC)系统中的空气处理单元(AHU)提出了一种基于自适应神经网络(NN)的送风温度控制器。 AHU中的热交换动力学非常复杂,几乎无法精确建模。而且,它受到多个外部干扰变量的影响。为了适应这种不确定性,引入了基于两层NN的直接自适应控制器,以在变化的运行条件下维持所需的送风温度。为了验证所提出方案的性能,已在试验性HVAC系统上进行了广泛的实验。实验结果证实,在迅速改变工作条件和对外部干扰的鲁棒性方面,我们的方法优于常规的比例-积分-微分控制器。

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