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Optimal parameter prediction method for multi-model wheat seedling growth chamber based on Kalman filter

A Kalman filter, Kalman filter technology, applied in instruments, simultaneous control of multiple variables, control/regulation systems, etc., can solve problems such as large temperature and humidity ranges

Active Publication Date: 2022-04-29
JIANGNAN UNIV +3
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] However, the suitable temperature and humidity range given by the above-mentioned existing research is relatively large, and the growth process of wheat seedlings is also affected by many other factors. The quality of wheat seedlings

Method used

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  • Optimal parameter prediction method for multi-model wheat seedling growth chamber based on Kalman filter
  • Optimal parameter prediction method for multi-model wheat seedling growth chamber based on Kalman filter
  • Optimal parameter prediction method for multi-model wheat seedling growth chamber based on Kalman filter

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Embodiment 1

[0056] This embodiment provides a method for predicting optimal parameters of a multi-model wheat seedling growth chamber based on the Kalman filter, see figure 1 , the method includes:

[0057] S1: Collect the temperature, humidity and CO in the growth chamber through the corresponding sensors set in the growth chamber of wheat seedlings 2 Concentration value;

[0058] S2: For temperature, humidity, CO 2 The measured value of the concentration sensor establishes the state equation and observation equation of the Kalman filter system;

[0059] Equation of state:

[0060] x k =AX k-1 +BU k-1 +W k-1 (1)

[0061] Observation equation:

[0062] Z k =HX k +V k (2)

[0063] Among them, X k ,Z k temperature, humidity and CO 2 Concentration predicted value and measured value matrix, A and B are the state parameters connecting k time and k-1 time, U k is a matrix composed of control quantities, W k is the process noise matrix at time k, V k is the observation noise...

Embodiment 2

[0083] The present embodiment provides a method for predicting optimal parameters of a multi-model wheat seedling growth chamber based on a Kalman filter, the method comprising:

[0084] Use corresponding sensors to collect temperature, humidity and CO in the wheat seedling growth chamber 2 concentration;

[0085] First, a certain process noise and measurement noise of the measured value of the sensor are eliminated through the Kalman filter, and then it and other environmental parameters that affect the growth of wheat seedlings include: NaCl concentration, light-to-dark ratio, light cycle, seed weight, etc. Regression (Nonlinear regression, NLR) and multilayer perceptron (Multilayerperceptron, MLP), radial basis function (Radial basis function, RBF) input parameters of the three models to predict the average height and weight of wheat seedlings after a period of growth of wheat seedlings Dry ratio to seed weight. The model with the best fitting effect is selected to predic...

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Abstract

The invention discloses a multi-model wheat seedling growth cabin optimal parameter prediction method based on a Kalman filter, which belongs to the field of intelligent equipment optimization. By using the Kalman filter to filter the data collected by the sensor in the growth chamber system, the value obtained by the Kalman filter is closer to the real value than the value directly collected by the sensor, which is conducive to the accuracy of temperature, humidity and CO2 concentration in the growth chamber system. control. Then, considering that the growth of wheat seedlings is a multi-influencing factor, NaCl concentration, light-to-dark ratio, light cycle, and seed weight were input into multiple nonlinear regression, radial basis neural network, and multilayer perceptron neural network models for prediction. Select a better model structure to more accurately find the optimal environmental parameters for the growth of wheat seedlings, and provide a certain reference for the germination and growth environment of wheat seedlings.

Description

technical field [0001] The invention relates to a method for predicting optimal parameters of a multi-model wheat seedling growth chamber based on a Kalman filter, and belongs to the field of intelligent equipment optimization. Background technique [0002] Wheat seedlings have high nutritional value. In some areas where grassland is scarce, artificially cultivated barley seedlings are needed as feed for herbivores such as cattle and sheep. Therefore, the environment for the growth of barley seedlings has become the focus of research. Previous studies have found that the optimum temperature for barley seed germination is 15-25°C, and the optimum humidity for seed germination is 80%-100%. Therefore, a suitable growth condition can be provided for the wheat seedlings by arranging sensors in the growth cabin plus control equipment. [0003] However, the suitable temperature and humidity range given by the above-mentioned existing research is relatively large, and the growth p...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D27/02
CPCG05D27/02
Inventor 李正权黄云龙周燕萍孙煜嘉马可陆波丁文杰
Owner JIANGNAN UNIV