Large greenhouse PD control system and method based on neural network

Abstract

The invention relates to the technical field of agricultural production, and particularly discloses a large greenhouse PD control system and method based on a neural network, and the system comprises an acquisition terminal which comprises a data acquisition control module and a plurality of sensor groups arranged in a greenhouse; the data acquisition control module is used for controlling the sensor group to acquire the internal environment information of the greenhouse in different time sequences; the user terminal is used for sending crop information of crops planted in the greenhouse to the server; an error feedback module is used for calculating an error feedback value according to the expected environment information and the internal environment information; a control parameter analysis module is used for performing control parameter analysis on the environment information and the expected environment information through a preset control parameter analysis model to obtain control parameters, and the control parameters comprise adjustment parameters of illumination intensity, temperature and humidity; and a PD control module is used for performing PD control on the environment adjusting equipment according to the control parameters and the error feedback values. By adopting the technical scheme of the invention, the time for controlling and adjusting the PD is shortened.

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...

Examples

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 ...

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...

Examples

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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