Crop response-driven intelligent coordination and optimization control of greenhouse microclimate factors

Authors

  • Qiuhui Liu 1. Institute of Mechanical and Electrical Engineering, China Jiliang University, 310018 Hangzhou, China;
  • Ying Zhang 1. Institute of Mechanical and Electrical Engineering, China Jiliang University, 310018 Hangzhou, China;
  • Binrui Wang 1. Institute of Mechanical and Electrical Engineering, China Jiliang University, 310018 Hangzhou, China; 2. Zhejiang Province Key Laboratory of On-line Testing Equipment Calibration Technology Research,China Jiliang University, 310018 Hangzhou, China
  • Lina Wang 1. Institute of Mechanical and Electrical Engineering, China Jiliang University, 310018 Hangzhou, China; 2. Zhejiang Province Key Laboratory of On-line Testing Equipment Calibration Technology Research,China Jiliang University, 310018 Hangzhou, China

Abstract

How to achieve precise and coordinated control of greenhouse microclimate factors under strong coupling and nonlinear conditions remains a key challenge in protected agriculture. To address this issue, this study integrates intelligent control and multi-objective optimization to regulate greenhouse temperature and humidity in a coordinated manner. A mechanistic model of a Venlo-type greenhouse was first developed in Matlab R2022a. Then, three control methods, namely LQR, MPC, and NMPC, were compared, and NMPC showed the best performance. Finally, NSGA-II was introduced to optimize the objective function weights of NMPC, further improving the control results. Compared with NMPC alone, the optimized method reduced the RMSE and MAE by 0.3366 and 0.0812 for temperature control, and by 0.2192 and 0.6853 for humidity control, respectively. The proposed method improves the precision and coordination of greenhouse environmental control and provides support for efficient greenhouse production. Ultimately, this study offers a promising technical paradigm for transitioning traditional greenhouse management towards highly autonomous and sustainable precision agriculture.      

Keywords: intelligent greenhouse, crop response, environmental regulation, coordinated optimization

DOI: 10.25165/j.ijabe.20261903.9239

Citation: Liu Q H, Zhang Y, Wang B R, Wang L N. Crop response-driven intelligent coordination and optimization control of greenhouse microclimate factors. Int J Agric & Biol Eng, 2026; 19(3): 133–138.

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Published

2026-07-14

How to Cite

(1)
Liu, Q.; Zhang, Y.; Wang, B.; Wang, L. Crop Response-Driven Intelligent Coordination and Optimization Control of Greenhouse Microclimate Factors. Int J Agric & Biol Eng 2026, 19, 133-138.

Issue

Vol. 19 No. 3 (2026): IJABE

Section

Animal, Plant and Facility Systems

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Copyright (c) 2026 International Journal of Agricultural and Biological Engineering

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