Coordination Control of Greenhouse Environmental Factors
Coordination Control of Greenhouse Environmental Factors
复制标题
温室环境因素协调控制
DOI：
10.1007/s11633-011-0567-3
复制
发表时间：
2011-05-01
影响因子：
4.3
通讯作者：
Shen, Ming-Yu
中科院分区：
文献类型：
--
作者：
Chen, Feng;Tang, Yong-Ning;Shen, Ming-Yu
Optimal control of greenhouse climate is one of the key techniques in digital agriculture. Greenhouse climate, a nonlinear and uncertain system, consists of several major environmental factors such as temperature, humidity, light intensity, and CO2 concentration. Due to the complex coupled correlations, it is a challenge to achieve coordination control of greenhouse environmental factors. This paper proposes a model-free coordination control approach for greenhouse environmental factors based on Q-learning. Coordination control policy is found through systematic interaction with the dynamic environment to achieve optimal control for greenhouse climate with the control cost constraints. In order to decrease systematic trial-and-error risk and reduce the computational complexity in Q-learning algorithm, case-based reasoning (CBR) is seamlessly incorporated into the Q-learning process. The experimental results demonstrate that this approach is practical, highly effective and efficient.
