文章基本信息

标题：Incremental Auto Regressive Prediction Models with External Variables of Greenhouse Air Temperature for Control Purposes
本地全文：下载
作者：Zhenfeng Xu ; Junjie Chen ; Jingxia Zhang 等
期刊名称：International Journal of Smart Home
印刷版ISSN：1975-4094
出版年度：2016
卷号：10
期号：9
页码：45-58
出版社：SERSC
摘要：The impact of actuators should be considered in the prediction modeling of greenhouse air temperature. In this paper, the operating state of a greenhouse was divided into five sub-states based on the on-off characteristic of actuators. A group of novel incremental auto regressive models with external variables (IARX models) suitable for the five operat-ing sub-states were deduced from the mechanistic modeling of greenhouse air tempera-ture. The new IARX models have fewer coefficients than other known ARX models. In or-der to validate the IARX prediction models, the related environmental factors of a glass greenhouse were measured. The prediction results of the IARX models were compared with two typical ARX models. The maximum prediction errors and the mean square errors of the IARX models, under the three operating sub-states of passive state(all actuators are not working), mechanical ventilation and fan-pad cooling, are 0.1°C, 0.14°C, 0.7°C, and 0°C, 0.3°C, 0.4°C, respectively. The prediction results are much better than those of onecompared model, while similar with the other.
关键词：Incremental ARX models; mechanistic model; system identification; tempe;r-;ature; prediction.