Neuron adaptive PID control for greenhouse environment

被引：18
|
作者：
Wang, Wei [1 ]
Xu, Lihong [1 ]
Hu, Haigen [2 ]
机构：
[1] Tongji Univ, Dept Control Sci & Engn, Shanghai 200092, Peoples R China
[2] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou 310023, Zhejiang, Peoples R China
来源：
JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING | 2015年 / 32卷 / 05期
关键词：
greenhouse environmental control; single neuron; self-tuning PID control; Hebb learning algorithm;
D O I：
10.1080/21681015.2015.1048752
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this article, a single neuron adaptive proportional, integral, and derivative (PID) control scheme is proposed for a greenhouse environment control problem by employing Hebb learning algorithm for tuning the parameters of the controller. The proposed scheme takes the advantage of the ability of neuron, such as adaptivity, self-organizing, and selflearning, and it is easily implemented and has been successfully applied to a greenhouse climate control problem. The results show that the proposed adaptive PID control scheme can provide better closed-loop performance compared with the conventional PID method.
引用
收藏
页码：291 / 297
页数：7
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