摘要
针对菇房空调系统在传统控制模式下易出现温度波动较大、运行能耗较高等问题,提出一种基于模型预测控制(Model Predictive Control,MPC)的食用菌工厂化菇房空调控制方法。首先基于等效电路法建立菇房阻容温度预测模型,利用遗传算法(Genetic Algorithms,GA)辨识模型内未知参数,建立以温度控制精度及系统能耗为优化方向的目标函数,然后以预测模型输出作为目标函数输入,最后通过粒子群优化算法(Particle Swarm Optimization,PSO)求解该目标函数,得到空调系统控制时域内的最优控制量。结果表明:基于MPC的温度控制方法能够有效在降低空调系统能耗的基础上提高温度控制精度,相较于传统阈值控制在温度控制精度上,平均绝对误差降低77%;在运行时间上,MPC控制方法平均每日能够减少1.2 h的压缩机运行时间,可节省10.4 kWh的电能。
Aiming at the problems of large temperature fluctuation and high energy consumption of mushroom room air conditioning system under the traditional control mode,a Model Predictive Control(MPC)-based temperature control method for mushroom room in edible mushroom factory is proposed.Firstly,a prediction model of mushroom room resistance and capacitance temperature based on the equivalent circuit method was established,the unknown parameters in the model were identified by using Genetic Algorithms(GA),an objective function with temperature control accuracy and system energy consumption as the optimization direction was established,and then the output of the prediction model was taken as the input of the objective function.Finally,the Particle Swarm Optimization(PSO)algorithm was used to solve the objective function and to obtain the optimal control amount in the time domain of the air conditioning system control.The experimental results showed that the MPC-based temperature control method could effectively improve the temperature control accuracy and reduce the energy consumption of the air conditioning system.The average absolute error of temperature control accuracy is reduced by 77% compared with the traditional threshold control method.In terms of running time,the MPC control method can reduce the compressor operation time by 1.2 h per day on average,and save 10.4 kWh of electric power.
作者
邹宇航
王明飞
张馨
王利春
魏晓明
郑文刚
Zou Yuhang;Wang Mingfei;Zhang Xin;Wang Lichun;Wei Xiaoming;Zheng Wengang(College of Engineering,Huazhong Agricultural University,Wuhan,430070,China;Intelligent Equipment Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing,100097,China;Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing,100097,China)
出处
《中国农机化学报》
北大核心
2024年第6期98-105,共8页
Journal of Chinese Agricultural Mechanization
基金
国家食用菌产业技术体系项目(CARS—20)
农业物联网技术北京市工程实验室建设项目(PT2022—27)
北京市食用菌创新团队项目(BAIC03—2022)。
关键词
菇房
模型预测控制
阻容模型
遗传算法
粒子群优化算法
mushroom house
model predictive control
resistance-capacitance model
Genetic Algorithm
Particle Swarm Optimization
