文献类型：会议论文

英文题名：Temperature and humidity control with a model predictive control method in the air-conditioning system

作者：Jingyun, Liu[1]; Ping, Li[1]

第一作者：刘景云

机构：[1] Logistics Department, College of Urban Rail Transit and Logistics, Beijing Union University, Beijing, China

第一机构：北京联合大学城市轨道交通与物流学院

会议论文集：2017 International Conference on Advanced Mechatronic Systems, ICAMechS 2017

会议日期：December 6, 2017 - December 9, 2017

会议地点：Xiamen, China

语种：英文

外文关键词：Air conditioning - Atmospheric humidity - Atmospheric temperature - Cost functions - Model predictive control - Particle swarm optimization (PSO) - Predictive control systems - Temperature - Thermal comfort - Three term control systems

摘要：Indoor air environment is usually controlled for occupants comfort with an air-conditioning (A/C) system. A model predictive control (MPC) method was proposed in this paper in order to control the air temperature and humidity which are coupled in the A/C system. Based on a multivariable control-oriented model, a controller was designed with a cost function. The control variables for the next control cycle were calculated by optimizing the cost function over a prediction horizon of 20s with a particle swarm optimization (PSO) algorithm. Different operation conditions of indoor air temperature and humidity were simulated in MATLAB to test the effectiveness of the control method. A PID control method was also used for the A/C system and simulated for comparison. Results showed that, the indoor air temperature and humidity could be well controlled with the proposed MPC method in the whole system operation range, and the MPC method showed better control performance than the PID control method. ? 2017 IEEE.