基于迭代学习的楼宇空调湿度控制研究

Research on humidity control of building air conditioning based on iterative learning

传统楼宇变风量空调控制方法,存在对被控系统数学模型的精度要求较高以及抗干扰能力弱的不足,因此限制了变风量空调系统的应用。针对变风量楼宇空调系统运行时存在的重复干扰与系统模型精度问题,采用迭代学习控制方法对变风量空调空气湿度进行控制。将变风量空调空气调节过程看成间歇过程,并且将室内空间湿度控制过程当作间歇过程对目标轨迹的跟踪问题,设计迭代学习控制器,使被控系统能够获得更好的精度和鲁棒性,实现变风量空调的高精度湿度轨迹跟踪。

The traditional control method of variable air volume(VAV) air conditioning in buildings has high requirements for the accuracy of the mathematical model of the controlled system and weak anti-interference ability,which limits the application of VAV air conditioning systems.In order to solve the problems of repeated interference and system model accuracy in the operation of the VAV building air conditioning system,the iterative learning control method is used to control the air humidity of the VAV air conditioning system.The air conditioning process of VAV air conditioning is regarded as an intermittent process,and the indoor space humidity control process is regarded as an intermittent process to track the target trajectory.Iterative learning controller is designed to enable the controlled system to obtain better accuracy and robustness,and achieve high-precision humidity trajectory tracking of VAV air conditioning.