This article presents an occupancy-based thermal modeling and HVAC control framework for large public indoor spaces characterized by rapidly changing human participation. A multi-zone ultrasonic door sensor system was used to enable real-time estimation of occupancy status, including conditions of wide doorways and multiple-person transitions. Field observations supported by thermal imaging were utilized to measure internal heat gains and initiate a dynamic thermal response model of the indoor environment. Based on these observations, a MATLAB-based heat transfer model was developed and integrated with an adaptive feedback control strategy that continuously adjusts HVAC operating parameters as a function of the estimated occupancy status. The model's performance was evaluated using robust error metrics, including the mean absolute deviation, demonstrating accurate temperature tracking under transient occupancy conditions. Simulation results indicated that the proposed adaptive control law can reduce HVAC energy consumption by approximately 20%–30% compared to fixed setpoint operation while maintaining thermal comfort. The results showed that the integration of occupancy assessment, dynamic thermal modeling, and adaptive control logic provides an effective and computationally lightweight approach to improving energy efficiency and indoor comfort in systems exposed to highly variable external influences.
Citation: Rashad Gasimov, Nurmammad Mammadov. Mathematical modelling and adaptive control of HVAC systems driven by ultrasonic sensor-based occupancy estimation[J]. Mathematical Modelling and Control, 2026, 6(3): 263-277. doi: 10.3934/mmc.2026020
This article presents an occupancy-based thermal modeling and HVAC control framework for large public indoor spaces characterized by rapidly changing human participation. A multi-zone ultrasonic door sensor system was used to enable real-time estimation of occupancy status, including conditions of wide doorways and multiple-person transitions. Field observations supported by thermal imaging were utilized to measure internal heat gains and initiate a dynamic thermal response model of the indoor environment. Based on these observations, a MATLAB-based heat transfer model was developed and integrated with an adaptive feedback control strategy that continuously adjusts HVAC operating parameters as a function of the estimated occupancy status. The model's performance was evaluated using robust error metrics, including the mean absolute deviation, demonstrating accurate temperature tracking under transient occupancy conditions. Simulation results indicated that the proposed adaptive control law can reduce HVAC energy consumption by approximately 20%–30% compared to fixed setpoint operation while maintaining thermal comfort. The results showed that the integration of occupancy assessment, dynamic thermal modeling, and adaptive control logic provides an effective and computationally lightweight approach to improving energy efficiency and indoor comfort in systems exposed to highly variable external influences.
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Rashad Gasimov, Nurmammad Mammadov. Mathematical modelling and adaptive control of HVAC systems driven by ultrasonic sensor-based occupancy estimation[J]. Mathematical Modelling and Control, 2026, 6(3): 263-277. doi: 10.3934/mmc.2026020
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