Fuzzy Model Predictive Control for a Comfort Air-Conditioning System

Yonghong Huang, Nianping Li, Yixun Yi, Jihong Zhan
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引用次数: 10

Abstract

Predictive control strategy is presented for a comfort air-conditioning system concerning energy performance and indoor comfort requirements. Predicted mean vote (PMV) index was incorporated into the control strategy to assess thermal comfort level. First-order linear reference trajectory was selected for the controlled variable PMV. And a zero-order Takagi-Sugeno fuzzy model, being linearized in real-time around the current operating point, was adopted as the predictive model. The experiment results indicate that the proposed techniques can save energy and improve indoor comfort significantly for air conditioning systems compared to the conventional PID control technique.
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舒适空调系统的模糊模型预测控制
针对某型舒适空调系统,提出了一种兼顾节能性能和室内舒适性要求的预测控制策略。将预测平均投票(PMV)指数纳入控制策略,评价热舒适水平。控制变量PMV选择一阶线性参考轨迹。采用围绕当前工作点实时线性化的零阶Takagi-Sugeno模糊模型作为预测模型。实验结果表明,与传统的PID控制技术相比,所提出的技术可以显著节约能源,提高空调系统的室内舒适度。
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