An Artificial Neural Network based Indoor Environment Control System

Abstract

Purpose: Various control methods based on specific conditions of building spaces have been studied to improve the performance of system’s operation and users’ comfort. The methods used in this research examine an improved control strategy for higher control precision not to increase system’s energy consumption, and lower energy consumption not to decrease its thermal comfort level. Method: This research proposes optimized supply air conditions to satisfy the indoor setting values by controlling the amount of supply air and its temperature, and investigates the auxiliary performance of an adaptive controller. Result: For maintaining thermal comfort levels, it is confirmed that an artificial neural network based controller is about 13% more efficient than two different controllers, but, for energy performance, it consumes more energy by about 12% to maintain indoor thermal comfort.