Optimal Feedback Control for HVAC Systems: An Integral Sliding Mode Control Approach Based on Barrier Function
Why this work is in the frame
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Bibliographic record
Abstract
Efficient control of air-handling units (AHUs) in heating, ventilating, and airconditioning (HVAC) systems is crucial for maintaining comfortable conditions while minimizing energy consumption. This study focuses on a multi-input multi-output (MIMO) control design for a nonlinear dynamic model of an AHU in a single thermal zone featuring variable air volume (VAV) properties in cooling mode. The goal is to develop decoupling controllers for the AHU by manipulating the airflow rate and cold water flow rate. An integral sliding mode control based on barrier function is proposed for regulating the humidity ratio of the thermal zone according to the desired characteristics. Subsequently, an integral sliding mode control based on barrier function is combined with an optimal feedback controller using a linear quadratic regulator (LQR) to manage indoor temperature. Additionally, an approximate classical sliding mode differentiator (ACSMD) is designed to estimate unmeasurable states that are used to construct the sliding variable of the second controller. The performance of the proposed control is evaluated through numerical simulations. Results demonstrate the ability of the controllers to guide the humidity and temperature of the thermal zone toward the required values without prior knowledge of the upper bounds on parameter variation, reducing chattering and yielding an optimal robust integral sliding mode control/LQR controller.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it