Large greenhouse pd control system and method based on neural network
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A neural network and control system technology, applied in the field of large greenhouse PD control systems, can solve problems such as long response time and easy overshoot, and achieve accurate results and avoid pests and diseases.
Active Publication Date: 2022-03-22
ZUNYI NORMAL COLLEGE
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[0005] In order to solve the technical problems of long response time and easy overshoot of greenhouse control adjustment, the present invention provides a large-scale greenhouse PD control system and method based on neural network
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Embodiment 1
[0069] Large-scale greenhouse PD control system based on neural network, such as figure 1 As shown, it includes acquisition terminal, user terminal, environmental regulation equipment and server, and the server includes a storage module, an error feedback module, a control parameter analysis module and a PD control module, wherein:
[0070] The acquisition terminal includes a data acquisition control module and several sensor groups arranged in the greenhouse. The sensor groups are networked through nodes, and the sensor groups are used to collect the care intensity, temperature and humidity of the greenhouse.
[0071] The data acquisition control module is used to control the sensor group to collect the internal environmental information of the greenhouse in time sequence, and the internal environmental information includes the light intensity, temperature and humidity in the greenhouse;
[0072] The user terminal is used to send the crop information of the crops planted in t...
Embodiment 2
[0103] The difference with Embodiment 1 is that: if figure 2 As shown, it also includes a blowing device arranged in the greenhouse, the wind blown by the blowing device is hot air, and the server also includes a wind control module, a pest detection module, a pest analysis module and an image acquisition control module; the acquisition terminal also includes a positioning module and A camera installed in the greenhouse;
[0104] The collection terminal is also used to collect the external environmental information of the greenhouse, which includes the light intensity, temperature and humidity outside the greenhouse;
[0105]The positioning module is used to collect the location information of farmers entering the greenhouse, and send the collected location information to the server. Specifically, the positioning module includes a Bluetooth beacon and a Bluetooth gateway laid in the greenhouse. The Bluetooth beacon in the greenhouse continuously broadcasts signals and data ...
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Abstract
The invention relates to the technical field of agricultural production, and specifically discloses a neural network-based large-scale greenhouse PD control system and method, including that the acquisition terminal includes a data acquisition control module and several sensor groups arranged in the greenhouse; the data acquisition control module is used for The sensor group is controlled in time sequence to collect the internal environmental information of the greenhouse; the user terminal is used to send the crop information of the crops planted in the greenhouse to the server; the error feedback module is used to calculate the error feedback value according to the expected environmental information and internal environmental information; the control parameters The analysis module is used to analyze the control parameters of the environmental information and the expected environmental information through the preset control parameter analysis model to obtain the control parameters. The control parameters include the adjustment parameters of the light intensity, temperature and humidity; The error feedback value carries out PD control on the environment regulating equipment. Adopting the technical scheme of the invention shortens the time for PD control adjustment.
Description
technical field [0001] The invention relates to the technical field of agricultural production, in particular to a neural network-based large greenhouse PD control system and method. Background technique [0002] With the development of the economy, people's living standards are getting higher and higher. Compared with ordinary seasonal fruits and vegetables, off-season fruits and vegetables are more popular. However, this kind of off-season products need to be very strict when planting Environmental conditions such as intensity of care, temperature, humidity, etc., people have been able to use intelligent control methods, and after training the system, they can simulate the intelligent control of the greenhouse system by humans. In the case of greatly reducing the labor force, You can also harvest more products. The traditional control method belongs to the posterior control method, the response time of the control is long and it belongs to the remedial control method. Amo...
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