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Modeling and predictive control of greenhouse temperature-humidity system based on MLD and time-series

机译:基于MLD和时间序列的温室温度湿度系统建模与预测控制

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摘要

Aiming at the hybrid properties of greenhouse temperature-humidity control system, predictive control based on mixed logical dynamical (MLD) model was researched. Firstly, hybrid system model of greenhouse temperature-humidity system was built based on MLD, and two subsystems of greenhouse temperature-humidity system were identified by forgetting factor recursive least squares (FFRLS) under the conditions of open ventilating window and closed ventilating window, respectively. Secondly, predictive control problem was described as mixed integer quadratic problem (MIQP), in which there were measurable but uncontrollable outside disturbance inputs including outside temperature, humidity, solar radiation and wind speed, etc. Time-series models were adopted to predict the disturbance inputs, then by branch & bound algorithm, MIQP was solved to obtain an optimal switching control sequences, based on which finite-time stability of the MLD system was analyzed and simulation control results were compared between the optimal switching signal and two given ones to verify the effectiveness of the methods achieved in this paper.
机译:针对温室温度湿度控制系统的杂交特性,研究了基于混合逻辑动力学(MLD)模型的预测控制。首先,基于MLD建立了温室温度湿度系统的混合系统模型,并通过分别在打开通风窗口和闭合通风窗口条件下忘记因子递归最小二乘(FFRLS)来识别温室温度湿度系统的两个子系统。其次,预测控制问题被描述为混合整数二次问题(MIQP),其中有可测量但无法控制的外部干扰输入,包括外部温度,湿度,太阳辐射和风速等。采用时间序列模型来预测扰动输入,然后通过分支和绑定算法,解决了MIQP以获得最佳开关控制序列,基于分析了MLD系统的有限时间稳定性,并在最佳开关信号和两个给定的仿真之间进行了仿真控制结果来验证本文实现了方法的有效性。

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