Greenhouse environment intelligent control method based on global variable prediction model

Abstract

The invention belongs to the technical field of facility agriculture environment control, and environment factors such as temperature, humidity, illumination intensity, CO2 concentration and the like in a greenhouse can be intelligently controlled. According to the greenhouse environment intelligent control method, a concept of a global variable is set, internal and external environment parameters in the greenhouse, current operating states of all controllers and local weather forecast for the next eight hours are used as all variables of a system, so as to be called global variables; and on this basis, a greenhouse environment prediction model based on the global variables is provided, and a BP (Back Propagation) artificial neural network is adopted to establish the model. By utilizing the model and combining fuzzy control, the greenhouse environment control method based on the global variables is invented. The greenhouse environment control method comprises the following steps that all of the global variables are used as input values, internal environment states of the greenhouse are predicted, and advanced adjustment is performed by the controllers in accordance with prediction results. By using the greenhouse environment intelligent control method, the problems of response lag, passive adjustment, inconsistent adjustment of the controllers and the like of traditional greenhouse environment control are solved, lag and oscillation in a response process are reduced, and the quality control of the greenhouse is improved.

Description

technical field [0001] The invention belongs to the technical field of facility agricultural environment control, and can intelligently control environmental factors such as temperature, humidity, light intensity and CO2 concentration in a greenhouse. The invention is suitable for the greenhouse environment control system with lagging response, passive adjustment, multiple input and multiple output, and difficult to establish an accurate mathematical model. Background technique [0002] The greenhouse environment control system needs to control the actuator to make corresponding adjustments according to the changes in the climate environment of the greenhouse: when the temperature is too low, it is necessary to use the heating system to supplement the temperature; Cooling devices, etc., to avoid overheating. In most of the greenhouse control systems nowadays, each actuator is usually controlled individually according to its actual measured value and set value. This convent...

AI Technical Summary

Problems solved by technology

[0003] According to the characteristics of the climate environment inside the greenhouse, the present invention proposes a new type of environmental control method based on the global variable prediction model, which is different from the traditional control method based on the current actual environmental variables. Variables, and take the global variable of greenhouse environment control as input, use BP artificial neural network to build a prediction model to predict the future state of the greenhouse internal environment, based on the predicted value, use fuzzy control to adjust the internal climate environment of the greenhouse, avoiding traditional greenhouse control Problems such as system response lag, passive adjustment, and uncoordinated controller adjustment reduce the hysteresis and oscillation in the response process and improve the control quality of the greenhouse. The specific structure is as follows: figure 1 shown

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