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Multi-model fractional order weight prediction function control method of electric heating furnace

A control method and weighted prediction technology, applied in the field of automation, can solve problems such as hindering the development of controllers and difficult to achieve modeling accuracy of nonlinear systems

Active Publication Date: 2016-09-28
HANGZHOU DIANZI UNIV
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Problems solved by technology

Although many achievements have been made in nonlinear research in recent years, the accuracy of nonlinear system modeling is difficult to achieve, which hinders the development of controllers.

Method used

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  • Multi-model fractional order weight prediction function control method of electric heating furnace
  • Multi-model fractional order weight prediction function control method of electric heating furnace
  • Multi-model fractional order weight prediction function control method of electric heating furnace

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Embodiment Construction

[0065] The main idea of ​​the present invention is to divide the entire working area into several sub-areas according to a certain method, and establish a corresponding fractional order model in each sub-area and control it in combination with a predictive function. Therefore, the original nonlinear model is converted into a linear fractional order model, the accuracy of the model avoids the complexity of nonlinearity, and effectively solves the problem of low model accuracy in industrial engineering that affects product quality. The specific steps are:

[0066] 1 Establish the multi-model structure of the electric heating furnace.

[0067] 1.1 According to the working temperature range of the electric heating furnace, the working area is divided into i equal parts, and i is the number to be divided into equal parts.

[0068] 1.2 Collect the real-time step response data of the electric heating furnace in each equally divided interval, and use the data to establish the fractio...

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Abstract

The invention discloses a multi-model fractional order weight prediction function control method of an electric heating furnace. First of all, a work temperature interval of the electric heating furnace is divided into several subintervals, then, fractional order models are established on the corresponding subintervals, then by use of an Oustatloup approximation method, the fractional order models are converted into high-order integer models, by use of a prediction control function method, a controller of each interval is designed, finally, according to errors between the models and actual objects, a proportion factor of each model is established, and accordingly, controller input of a multi-model structure is obtained. According to the invention, a local state space model of a controlled object is established and a previous nonlinear model is converted into a linear local model, such that the control performance of a system is improved, and at the same time, application of a model prediction control method in a fractional order system is facilitated.

Description

technical field [0001] The invention belongs to the technical field of automation and relates to a multi-model fractional order weighted prediction function control method for an electric heating furnace. Background technique [0002] The temperature control system is an important process link in industrial control. Since the accuracy of temperature control has an important impact on the quality and quality of the produced products, improving the accuracy of control is a goal we are increasingly pursuing. The electric heating furnace is the most commonly used device in industrial temperature control. However, the object of the electric heating furnace presents characteristics such as strong nonlinearity, large operating range, and large delay. The heating furnace, a nonlinear system, has received attention. Although many achievements have been made in nonlinear research in recent years, the accuracy of nonlinear system modeling is difficult to achieve, which hinders the dev...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04G05D23/19
CPCG05B13/048G05D23/1919
Inventor 张日东张俊锋徐卫德
Owner HANGZHOU DIANZI UNIV
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