Model-based adaptive controller for personalized ventilation and thermal comfort in naturally ventilated spaces

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Tsinghua University

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This work develops a standalone autonomously controlled personalized ventilation (PV) unit in a naturally ventilated (NV) office space to maintain acceptable thermal comfort (TC) under steady and transient indoor conditions and activity levels. The NV-PV proportional integral derivative (PID) controller adjusts the PV supply temperature (TSPV) at the occupant set flow rate (QSPV) based on predicted TC using a regression model. The target TC level that the controller attains at all times is between 0 (neutral) and 1 (slightly comfortable). Process transfer functions were developed and then used to find the adaptive PID tuning coefficients using the Internal Model Control (IMC) method. The controller was tested in a case study at indoor temperature range of 25 to 33 °C with relative humidity range of 55% and 80%. It was shown that the NV-PV controller adjusted TSPV to maintain acceptable TC under transients of indoor conditions and metabolic rates. © 2021, Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature.

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Adaptive pid controller, Natural ventilation, Personalized ventilation, Thermal comfort, Controllers, Model predictive control, Office buildings, Proportional control systems, Regression analysis, Thermal conductivity, Two term control systems, Ventilation, Adaptive controllers, Indoor temperature, Internal model control, Proportional integral derivative controllers, Relative humidity range, Steady and transient, Supply temperatures, Humidity control

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