摘要
针对空调在保证送风温度的基础上,实现室内负荷的变更与控制系统应对外界随机干扰的需求,文中提出一种基于迭代优化的空调温湿度控制算法。通过建立空调机的二维跟踪框架运行模型来设计迭代学习算法实现空调机运行状态的控制,并通过在迭代优化学习的过程中加入预测控制环节来减小随机干扰带来的影响。仿真实验以及对比不同干扰下的空调运行响应结果表明,所提出的方法不仅能够抵抗周期性干扰的影响,而且在随机干扰环境下仍然能够保持良好的跟踪控制性能。
A temperature⁃humidity control algorithm based on iterative optimization is proposed to make the air conditioning realize the change of indoor load and the demand of control system to deal with external random interference on the basis of ensuring the air supply temperature.The iterative learning algorithm is designed by establishing the two⁃dimensional tracking frame operation model of the air conditioner to control the operation state of the air conditioner,and the predictive control link is added in the process of iterative optimization learning to reduce the influence of random interference.The results of the simulation experiments and the comparison of air⁃conditioning operation response under different disturbances show that,the proposed method can not only resist the influence of periodic disturbances,but also maintain good tracking control performance in the random interference environment.
作者
文丹
WEN Dan(School of Information Science and Technology,Guilin University of Electronic Technology,Guilin 541004,China)
出处
《现代电子技术》
北大核心
2020年第24期38-41,共4页
Modern Electronics Technique
基金
广西创新驱动发展专项(科技重大专项)项目(桂科AA17204006)
广西高等学校千名中青年骨干教师培育计划人文社会科学类立项课题(2020QGRW037)。
关键词
空调
温湿度控制
迭代优化
运行控制
随机干扰
仿真实验
air⁃conditioning
temperature⁃humidity control
iterative optimization
operation control
random interference
simulation experiment
