Fuzzy control method and system based on successive type fuzzy interpolation

A technology of fuzzy control and fuzzy control quantity, applied in general control system, control/regulation system, adaptive control and other directions, can solve the problems of fuzzy reasoning information loss, poor control accuracy, etc., to achieve fast response speed and strong anti-interference ability , the effect of high control precision

Inactive Publication Date: 2009-04-22
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to propose a fuzzy control method and system based on continuous fuzzy interpolation based on the relative similarity of fuzzy sets in view of the above-mentioned deficiencies in the prior art, so as to solve the problem of

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  • Fuzzy control method and system based on successive type fuzzy interpolation
  • Fuzzy control method and system based on successive type fuzzy interpolation
  • Fuzzy control method and system based on successive type fuzzy interpolation

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Embodiment Construction

[0012] The implementation of the present invention will now be described in detail in conjunction with the accompanying drawings and embodiments.

[0013] Such as figure 1 Shown is a fuzzy control system module structure diagram based on continuous fuzzy interpolation. The present invention uses sensors to extract on-line control object related parameters in the industrial field control process as system input (input includes temperature, pressure, liquid level, etc.), and calculates Its deviation and the rate of change of the deviation; the deviation and the rate of change of the deviation are quantified within the value range to obtain finite discrete values, which constitute the discrete domain of controller input, which is determined by the empirical data and rule base through the center of gravity method. Clear processing, the query module establishes the fuzzy control quantity query table of the relationship between the deviation fuzzy quantity, the deviation change rate...

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Abstract

The invention discloses a fuzzy control method of continuous fuzzy interpolation based on relative similarity of a fuzzy set and a system thereof, and relates to the industrial control field. The method comprises the following steps: establishing a continuous fuzzy mapping relation between an input variable and a control variable of a fuzzy controller; performing interpolation computation on a control value based on a similar priority principle according to the relative similarity relation of the fuzzy set in a fuzzy bunch, thus achieving continuous precise control on a controlled object, and comprehensively and perfectly reserving the information from fuzzy reasoning. The method and the system have the advantages of strong anti-interference capability, fast response speed and high control precision, and can meet the actual requirements of the industrial control. The method is applicable to control systems, in which the input variable and the output control variable are continuous variables, especially furnace temperature control systems of large-sized and medium-sized heating furnaces in the industries such as metallurgical industry, chemical industry and the like.

Description

technical field [0001] The invention relates to the fields of control theory and control engineering. Background technique [0002] In the industrial production process, the control problem of single-parameter continuous input is a common and critical control problem, and most of them have characteristics such as nonlinearity, strong coupling, time-varying, and time-delay. Traditional PID control and other control methods are difficult to effectively control it. Fuzzy control method can make up for the defect that the precise mathematical model cannot be established in the single-parameter continuous input control system, so that the control effect and response speed are improved. However, in terms of steady-state precision control, the control effect of fuzzy control methods is usually not ideal. One of the main reasons is that the generation of fuzzy control variables based on some fuzzy inference rules is too rough to meet the actual requirements. The fuzzy control metho...

Claims

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Application Information

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IPC IPC(8): G05B13/02
Inventor 李银国罗蓉汤卓群陈和平薛文蒋畅江
Owner CHONGQING UNIV OF POSTS & TELECOMM
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