面向公共建筑空调末端控制器调适的自整定控制方法

Self-tuning Control Method for Air-conditioning Terminal Controller Commissioning in Public Buildings

公共建筑空调室温调控过程具有强烈的非线性特征,难以建立其精确数学模型,并以此为依据实施在线控制。在实际应用中,工程技术人员只能借助经验完成控制器参数整定工作,费时费力且难以达到预期的效果。为此,以变风量空调系统为研究对象,本文提出了1种基于物理-数据驱动混合模型的自整定控制方法,进一步开展传统基于经验的串级PI方法与提出自整定方法的对比试验研究。结果表明,在无人参与的条件下,该方法能够实现空调末端控制器参数的在线自整定。提出方法不仅有利于提升公共建筑空调系统调适效率,还有利于提升系统运行水平。

Since indoor temperature control process of air conditioning has strong nonlinear characteristics,it is difficult to build precise mechanism model and to implement corresponding online control.In practical,the tuning working of controller parameters has to be achieved based on human experience,which not only need consume large number of time but also maybe difficult to obtain a satisfactory result.Thus,taking the variable air volume air-conditioning system as the study object,a self-tuning control method based on the physical-data driven hybrid model was proposed in this paper.Then,the comparative experimental studies are carried out between conventional experience-based cascade PI method and the proposed method.Results indicate that the proposed method can realize the self-tuning for the terminal controller parameters.The proposed method not only will be benefit for improving commissioning efficiency of large-public building air-conditioning system,but also can improve the system operation level.