Greenhouse environment optimization control method based on multi-target grey particle swarm algorithm
A particle swarm algorithm and optimization control technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., to achieve the effect of improving accuracy, saving electricity costs, and saving energy costs
Inactive Publication Date: 2017-08-11
ANHUI AGRICULTURAL UNIVERSITY
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[0005] The purpose of the present invention is to provide a greenhouse environment optimization control method based on the multi-objective gray particle swarm algorithm to solve the deficiencies in the prior art greenhouse control method
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[0074] Step 1: Test environment and data collection
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The invention discloses a greenhouse environment optimization control method based on a multi-target grey particle swarm algorithm. Through introducing manual control factors, based on an extended autoregressive model ARX, a temperature, humidity and energy consumption cost multi-target model function is constructed, a grey association theory and a particle swarm optimization algorithm PSO are utilized, and multi-target optimization control on the greenhouse environment model is carried out. The greenhouse environment optimization control method is advantaged in that greenhouse electricity cost can be saved to a certain degree, and reference is provided for reasonable greenhouse environment regulation and control.
Description
technical field [0001] The invention relates to the field of greenhouse environment control methods, in particular to a greenhouse environment optimization control method based on a multi-objective gray particle swarm algorithm. Background technique [0002] Greenhouse crop production is a highly intensive facility industry. Compared with field crops, greenhouse production is not easily disturbed by the external climate and can meet the needs of producers in different development cycles for crops. The agricultural greenhouse regulates the environmental parameters of the greenhouse (such as temperature, humidity, carbon dioxide concentration, light conditions, etc.) . Most of the traditional greenhouse control modes rely on the prior knowledge of producers, which are highly subjective, poor in real-time, high in misjudgment rate, lack of scientific basis, and are not suitable for the needs of today's greenhouse production. At present, the key to solve the actual greenhouse ...
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Login to View More IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 张武张雪花杨旭王露娇蔡芮莹朱小倩胡玮炜
Owner ANHUI AGRICULTURAL UNIVERSITY