An efficient design of genetic algorithm based Adaptive Fuzzy Logic Controller for multivariable control of HVAC systems

Abstract

In Heating, Ventilating and Air Conditioning (HVAC) systems, effective thermal management is required because energy and operation costs of buildings are directly influenced by how well an air-conditioning system performs. HVAC systems are typically nonlinear time varying with disturbances, where conventional PID controllers may trade-off between stability and rise time. To overcome this limitation, a Genetic Algorithm based Adaptive Fuzzy Logic Controller (AFLC) design has been proposed for the control of temperature and relative humidity of an experimental setup by manipulating valve positions to adjust the water and steam flow rates for Air Handling Unit (AHU). Modulating equal percentage Globe valves for chilled water and steam have been modeled according to exact flow rates of water and steam. A novel method for the adaptation of Fuzzy Logic Controller (FLC) by modifying Fuzzy Rule Matrix (FRM) based on Genetic Algorithm (GA) has been proposed. The proposed adaptive controller outperforms the existing fuzzy controller in terms of steady state error, rise time and settling time.