Method of Model Predictive Control for Building Air-conditioning System Based on Fuzzy Interval Optimization

To further guarantee the thermal comfort requirements of indoor staff in office buildings, a predictive control method of building air conditioning system based on fuzzy interval optimization was proposed. First, based on the building operation data, fully considering the impact of differences in geographical location, climate environment and people on the feeling of comfort, the membership function of fuzzy rules was used to optimize the traditional comfort index, so as to clarify the temperature range of indoor people's comfortable feeling. Then, the model predictive control method was used to adjust the air-conditioning setting value, and the indoor comfortable temperature range was maintained by combining the interval control strategy. Finally, the proposed method was embedded in the smart building monitoring system to verify its advantaged and effectiveness, and the comfort satisfaction of indoor staff was improved by 34%. Results show that the fuzzy comfort zone proposed in this paper can better satisfy the comfortable feeling of indoor people, and integrated with the interval model predictive control method the control actions of the MPC controller can be reduced simultaneously.