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Temperature and humidity control method during a wood drying process based on combination of radial basis function (RBF) nerve network and proportional integral derivative (PID) closed loop control

A neural network, wood drying technology, applied in non-electric variable control, control/regulation systems, simultaneous control of multiple variables, etc., can solve problems such as poor control performance

Inactive Publication Date: 2012-03-28
任洪娥
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Problems solved by technology

[0004] The present invention aims to solve the problem of poor control performance of the existing wood drying control method based on the PID control method, thereby providing a wood drying machine control method based on the combination of RBF neural network and PID control

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  • Temperature and humidity control method during a wood drying process based on combination of radial basis function (RBF) nerve network and proportional integral derivative (PID) closed loop control
  • Temperature and humidity control method during a wood drying process based on combination of radial basis function (RBF) nerve network and proportional integral derivative (PID) closed loop control
  • Temperature and humidity control method during a wood drying process based on combination of radial basis function (RBF) nerve network and proportional integral derivative (PID) closed loop control

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specific Embodiment approach 1

[0029] Specific implementation mode 1. Combination figure 1 and figure 2 Illustrate this specific embodiment, based on the temperature and humidity control method in the wood drying process that RBF neural network and PID closed-loop control combine, described control method realizes by performing the following steps cyclically:

[0030] Step 1. Use thermocouples to collect the temperature y1 in the wood drying chamber, and calculate the temperature y1 and the temperature value yr1 input by the system to obtain the temperature control amount, and input the temperature control amount to the temperature PID controller and the temperature PID controller at the same time. Temperature neural network NN1;

[0031] Use the moisture content probe to collect the humidity y2 in the wood drying room, and calculate the humidity y2 and the temperature value yr2 input by the system to obtain the humidity control amount, and input the humidity control amount to the humidity PID controller ...

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Abstract

A temperature and humidity control method during a wood drying process based on combination of a radial basis function (RBF) nerve network and proportional integral derivative (PID) closed loop control relates to the temperature and humidity control method during a wood drying process. By using the current wood drying control method based on the PID control method, control performance is low. By using the method of the invention, the above problem can be solved. Based on the combination of the RBF nerve network and the PID control, closed loop adjustment of the temperature and humidity in a wood drying chamber can be achieved and the temperature and humidity control performance is good. By using the method, an adaptive ability and robustness of a control system can be improved. The method is suitable for the wood drying process.

Description

technical field [0001] The invention relates to a temperature and humidity control method in the wood drying process. Background technique [0002] The radial basis function (RBF-Radial Basis Function) neural network is a neural network proposed by J.Moody and C.Darke in the late 1980s. It is a three-layer feed-forward network, which realizes a network structure that can overlap and cover the receiving area by imitating the partial correction in the brain; the RBF neural network has the characteristics of local approximation, relative to the input local area, only Several connection weights affect the output of the network, thus allowing the neural architecture to learn quickly. Since the 1990s, neural networks have been widely studied, and they have made great progress in various fields. The method based on neural network has been applied in industrial control, but its control scheme needs to be further improved, and the hardware cost for realizing the scheme is relativel...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D27/00
Inventor 任洪娥陈龙徐达丽
Owner 任洪娥