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.