Heating, Ventilating and Air Conditioning (HVAC) systems have nonlinear character and nature. Current models for control components and the optimization of HVAC system parameters can be linear approximations based on an operating or activation point, or alternatively, highly complex nonlinear estimations. This duality creates problems when the systems are used with real time applications. The two parameters temperature and relative humidity (RH) have a more direct effect in most applications of HVAC systems than the execution. This study’s objective is to implement and simulate an adaptive controller for decoupled bi-linear HVAC systems for the purpose of controlling the temperature and RH in a thermal zone. The contribution of this study is to apply the adaptive controller for the decoupled bi linear HVAC system via relative gain array (RGA). To achieve this objective, we used a system identification toolbox to increase the speed and accuracy of the identification of system dynamics, as was required for simplification and decoupled HVAC systems. The method of decoupling is relative gain array. The results of the simulation show that when compared with a classical PID controller, the adaptive controller performance is superior, owing to the high efficiency with which the steady state set points for temperature and RH are reached.
Relative gain array estimation based on non-parametric frequency domain system identification
