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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:针对温室温湿度控制系统的混合特性,研究了基于混合逻辑动力学(MLD)模型的预测控制。首先,建立了基于MLD的温室温湿度系统混合系统模型,并在开窗和闭窗条件下,分别通过忘记因子递推最小二乘(FFRLS),确定了温室温湿度的两个子系统。 。其次,将预测控制问题描述为混合整数二次问题(MIQP),其中存在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干扰输入,然后通过分支定界算法,求解MIQP以获得最佳开关控制序列,在此基础上分析了MLD系统的有限时间稳定性,并比较了最佳开关信号和两个给定开关信号之间的仿真控制结果,以验证本文实现的方法的有效性。

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