Tube-Based Model Predictive Controller for Building's Heating Ventilation and Air Conditioning (HVAC) System

The proactive control of building's heating, ventilation, and air conditioning (HVAC) system can reduce energy consumption and provides cost saving. An efficient design of a controller for a complex system such as a building, which is also prone to uncertainties and disturbances, calls for advanced control methods such as model predictive control (MPC). This article presents a tube-based MPC to minimize the net cost of energy usage by the building's HVAC system while satisfying the comfort level of the building's occupants. Contrary to the conventional MPC, this controller is robust against model uncertainty and exogenous disturbances affecting the building thermal load model. Compared to other robust approaches such as the min-max controller, the proposed controller is of lower computational complexity and can be used with the environment having complex models, e.g., with nonlinear dynamics. Moreover, the proposed controller shows a satisfactory performance when optimizing an economic objective, such as cost minimization. The merits of using the proposed MPC controller are demonstrated using several simulation cases.

Automated summary

The article introduces a tube-based model predictive controller to minimize the net cost of energy usage by a building's HVAC system while ensuring comfort level. This controller is robust against model uncertainty and exogenous disturbances, suitable for environments with complex models.