Optimizing Occupant Comfort in a Room Using the Predictive Control Model as a Thermal Control Strategy

Area of Science:

• Building Science
• Control Engineering
• Environmental Psychology

Background:

• Achieving optimal thermal comfort is crucial for occupant well-being and building efficiency.
• User-centered building control is gaining traction, emphasizing personalized environmental settings.
• Existing strategies often struggle to balance thermal comfort with energy conservation effectively.

Purpose of the Study:

• To develop and implement an integrated thermal control strategy for enhanced user comfort and reduced energy consumption.
• To investigate the application of a hybrid control system incorporating Model Predictive Control (MPC) and fuzzy logic.
• To address the influence of room occupancy levels on thermal control performance.

Main Methods:

• Development of a hybrid control strategy combining Model Predictive Control (MPC) and fuzzy logic.
• Integration of environmental parameters and personal perception factors into the control algorithm.
• Implementation and case study within a laboratory room at the Technical University of Civil Engineering Bucharest.
• Consideration of room occupancy level as a key constraint.

Main Results:

• Demonstration of a functional thermal control strategy that optimizes for both comfort and energy savings.
• Validation of the hybrid MPC-fuzzy system's effectiveness in a real-world laboratory setting.
• Insights into the parameterization of fuzzy systems for adaptive building control.

Conclusions:

• The proposed hybrid control strategy effectively balances thermal comfort and energy reduction goals.
• The integration of MPC and fuzzy logic, considering occupancy, offers a promising approach for user-centered building management.
• Further research into fuzzy system parameterization can enhance the adaptability and performance of intelligent building controls.