Intelligent control method for grain drying tower based on neural network and fuzzy control

A technology of fuzzy control and neural network, applied in the direction of biological neural network model, adaptive control, general control system, etc., can solve the problem that PID control algorithm is difficult to achieve effective control

Inactive Publication Date: 2016-12-14
THE PLA INFORMATION ENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims at the problems that the grain drying process in the prior art is a typical nonlinear, multi-variable, large-delay, unsteady-state heat transfer and mass transfer process o...

Method used

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  • Intelligent control method for grain drying tower based on neural network and fuzzy control
  • Intelligent control method for grain drying tower based on neural network and fuzzy control
  • Intelligent control method for grain drying tower based on neural network and fuzzy control

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Experimental program
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Effect test

Embodiment 1

[0046] Example 1: Combining Figure 1-Figure 11, an intelligent control method for grain drying towers based on neural network and fuzzy control, the hardware includes temperature / moisture sensor, data acquisition and processing module, input and display module, temperature / moisture sensor collects temperature and moisture information, data acquisition and processing module The drying parameters are controlled according to the temperature and moisture information, and the input and display modules are used for human-computer interaction. It is characterized in that: the specific steps of the intelligent control method of the grain drying tower based on neural network and fuzzy control are: Step 1: Set the initial value of the drying data according to the drying experience;

[0047] Step 2: Carry out fuzzy control training on the system and draw the control rule table; mainly carry out the training of BP neural network, the specific steps are:

[0048] Step 201: Network initia...

Embodiment 2

[0069] Example 2: Combining Figure 1-Figure 11 , an intelligent control method for grain drying towers based on neural network and fuzzy control. The hardware includes temperature / moisture sensors, data acquisition and processing modules, input and display modules. reliability and anti-interference performance. At the same time, high-performance ARM is used for data collection and processing to ensure the real-time performance of data collection and processing. At the same time, the modular design is adopted, and each module has independent functions, and can realize self-inspection, report the self-inspection information, and the host computer forms the status information of the whole machine, which is convenient for the monitoring of the whole machine and troubleshooting and maintenance of the whole machine. The overall hardware architecture is designed as figure 1 shown.

[0070] Neural Network and Fuzzy Control Algorithm

[0071] Control algorithm Through the processi...

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Abstract

The invention belongs to the technical field of grain drying control and specifically relates to an intelligent control method for a grain drying tower based on neural network and fuzzy control. The hardware comprises a temperature/moisture sensor, a data collecting and treating module and an input and display module, wherein the temperature/moisture sensor is used for collecting temperature and moisture information; the data collecting and treating module is used for controlling the drying parameter according to the temperature and moisture information; the input and display module is used for performing man-machine interaction. The method comprises the following steps: 1) setting an initial value for the drying data according to a drying experience; 2) performing fuzzy control training on the system and drawing a control rule table; 3) sampling and correcting an error in the drying process. A drying tower is modeled according to the training data through the network; the error between a forecast moisture value after training and a moisture value calculated according to a model is small; the practical application requirement can be met; although a simple linear model is adopted, the training effect is excellent even if a higher order model is adopted.

Description

technical field [0001] The invention belongs to the technical field of grain drying control, in particular to an intelligent control method for a grain drying tower based on neural network and fuzzy control. Background technique [0002] There are more than 7,000 sets of large and medium-sized grain drying equipment in my country, and less than 5% of them are equipped with online moisture detection and control devices, which are basically controlled manually, which is likely to cause waste of grain due to excessive drying and energy waste caused by insufficient drying. The "Twelfth Five-Year Development Plan for the Grain Industry" issued by the National Development and Reform Commission and the State Grain Administration specifically puts forward the goal of improving the drying facilities. facilities, eliminate the drying capacity with backward technology, and keep the national drying capacity at more than 110 million tons, including more than 91 million tons in the northe...

Claims

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Application Information

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IPC IPC(8): G05B13/04G06N3/02
CPCG05B13/041G06N3/02
Inventor 刘拥军杨斌高博董春宵
Owner THE PLA INFORMATION ENG UNIV
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