WCSE 2019 SUMMER ISBN: 978-981-14-1684-2
DOI: 10.18178/wcse.2019.06.141

Research on Temperature Control System of Plant Factory Based on Particle Swarm Optimization

Shigang Cui , Jiejie Chen, Xingli Wu , Lin He , Yongli Zhang

Abstract— In order to solve the problems of complex temperature control and inaccurate regulation in plant factories, this paper starts from the actual model of plant factory, uses STM32 processor with embedded Cortex-M3 as the core, and collects the plant factory through Modbus fieldbus technology. Temperature information, using the MATLAB tool to derive the temperature control model of the plant growth cabinet. Finally, the fuzzy control algorithm and particle swarm optimization (PSO) optimization algorithm are used to control the temperature control model with two different PIDs. By establishing the MATLAB simulation model, the optimal control method under the plant growth cabinet model is obtained. The results show that compared with fuzzy PID, PID control based on PSO algorithm has good stability and regulation, and plants based on this environment can get better growth.

Index Terms— plant growth cabinet, temperature control, modbus fieldbus, PSO algorithm, fuzzy PID control

Shigang Cui , Jiejie Chen, Xingli Wu , Lin He , Yongli Zhang
Tianjin University of Technology and Education, Tianjin Key Laboratory of Information Sensing & Intelligent Control, CHINA

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Cite: Shigang Cui , Jiejie Chen, Xingli Wu , Lin He , Yongli Zhang, "Research on Temperature Control System of Plant Factory Based on Particle Swarm Optimization1," Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering, pp. 940-946, Hong Kong, 15-17 June, 2019.