An Automatic Plant Irrigation System Based on Fuzzy Control

Zhen Yang Ge; Rui Qing Zhang; Ying Jie Yu; Wang Wang Wu

doi:10.4028/www.scientific.net/AMM.303-306.1162

Paper Titles

A Method of Harmonic Current Suppression in Photovoltaic Grid-Connected Systems
p.1145

A New Automotive Electronic Control System Open Architecture
p.1149

A Research on the Fuzzy Control with Genetic Algorithm for Maximum Power Point Tracking of Photovoltaic Power System
p.1153

A Simulation Platform for Dynamic Positioning Ship with Guidance, Navigation and Control Function
p.1158

An Automatic Plant Irrigation System Based on Fuzzy Control
p.1162

An Improved Design for PID Controller Based on Viere Theorem
p.1167

Equivalent Model and Maximum Wind Power Tracking Control Mechanism of Grid-Connected PMSWG
p.1171

Model Reference Adaption Identification Control Research Based on the Asynchronous Motor Vector Control System Model
p.1175

Model-Free Adaptive Control Based on Particle Swarm Optimization Algorithm for Water Bath Drawing Process of Carbon Fiber
p.1180

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 303-306An Automatic Plant Irrigation System Based on...

An Automatic Plant Irrigation System Based on Fuzzy Control

Abstract:

An automatic watering controller with AT89S52 single-chip microcomputer was developed. According to the moisture condition detected by soil moisture sensor, the system could control the watering quantity by using fuzzy control rules to limit opening and closing time of electromagnetic valve of the irrigation system. Mamdani inference algorithm was employed as fuzzy control model for this closed-loop control system. Soil moisture sensor was put into the substrate for roots growth to obtain moisture information and used as the input. By comparing the water needed for plant growth, water demand and the electromagnetic valve opening and closing time was determined by the single-chip microcomputer program. Centroid method of defuzzification was used to determine the quantitative level of watering quantity. This fuzzy controller was designed by MATLAB fuzzy logic toolbox. The control system was simulated by Simulink. Simulation results show that this control method has good stability.

You might also be interested in these eBooks

Sensors, Measurement and Intelligent Materials

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 303-306)

Pages:

1162-1166

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.303-306.1162

Citation:

Cite this paper

Online since:

February 2013

Authors:

Zhen Yang Ge, Rui Qing Zhang, Ying Jie Yu, Wang Wang Wu

Keywords:

AT89S52 Chip, Fuzzy Control, Irrigation System, Soil Moisture Sensor

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] M. Bahat, G. Inbar, O. Yaniv, M. Schneider: Engineering Applications of Artificial Intelligence Vol. 13(2000) p.137.

DOI: 10.1016/s0952-1976(99)00053-6

Google Scholar

[2] Jiandong Hu, Tiecheng Duan and Jianhua Shi: Chinese Journal of Scientific Instrument Vol. 24 (2003), p.123(In Chinese).

Google Scholar

[3] C.J. Phene, DeTar, W.R., Clark, D.A.: Applied Engineering in Agriculture, Vol. 8(1992), p.787.

Google Scholar

[4] Yingshan Zhong, Jiaqiang Yang, Jinlian Deng: Transactions of the Chinese Society for Agricultural Machinery Vol. 32 (2001), p.75 (In Chinese).

Google Scholar

[5] Yingchuan Kuang, Yue Shen, Jiannan Duan: Transactions of the CSAE Vol. 27 (2011), p.18 (In Chinese).

Google Scholar

[6] Wei Zhang, Yong He, Zhengjun Qiu: Transactions of the CSAE Vol. 25 (2009), p.7 (In Chinese).

Google Scholar

[7] Ming Jiang, Qigong Chen, Xingfang Yan: Transactions of the CSAE Vol. 21 (2005), p.17 (In Chinese).

Google Scholar

[8] P. Javadi Kia, A. Tabatabaee Far, M. Omid, R. Alimardani and L. Naderloo: World Applied Sciences Journal Vol. 6 (2009), p.16.

Google Scholar