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

Abstract

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.