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This paper presents an occupancy-predicting control algorithm for heating,ventilation, and air conditioning (HVAC) systems in buildings. It incorporatesthe building's thermal properties, local weather predictions, and a self-tuningstochastic occupancy model to reduce energy consumption while maintainingoccupant comfort. Contrasting with existing approaches, the occupancy modelrequires no manual training and adapts to changes in occupancy patterns duringoperation. A prediction-weighted cost function provides conditioning of thermalzones before occupancy begins and reduces system output before occupancy ends.Simulation results with real-world occupancy data demonstrate the algorithm'seffectiveness.

Model Predictive HVAC Control with Online Occupancy Model