Layered fuzzy system based on unified model

A fuzzy system and fuzzy technology, applied in general control systems, control/regulation systems, instruments, etc., can solve problems such as reducing the number of inference rules, design complexity and real-time computing, and achieve the effect of strong practicability

Inactive Publication Date: 2008-02-06
ZHENGZHOU UNIV
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Problems solved by technology

[0006] The layered fuzzy system based on the unified model described in the present invention is mainly composed of the layered fuzzy system and the unified model. The application in the ultra-large-dimensional input system provides an effective method; the unified model provides a technical method for effectively applying the hierarchical fuzzy system to actual industrial production. Du

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  • Layered fuzzy system based on unified model
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  • Layered fuzzy system based on unified model

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[0016] The layered fuzzy system based on unified model of the present invention is to carry out according to the following steps:

[0017] The first step is to establish the structural model of the hierarchical fuzzy system

[0018] If the system has n physical input variables of x 1 、x 2 、……x n , using the layered fuzzy system shown in Figure 1, the basic fuzzy units of each layer have two input variables, where x 1 、x 2 As the input of the basic fuzzy unit of the first layer, its output y 1 and a third physical input variable x 3 As the input of the basic fuzzy unit of the second layer, the rest of the layers can be deduced by analogy. Therefore, the system of n-dimensional physical input variables can form n-1 layers with such a structure, and each layer has only two input variables.

[0019] Under this structure, the number of rules is the least. Assuming that each input variable has N fuzzy subsets and there are M input variables, the total number of rules is S=N 2...

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Abstract

The present invention discloses a hierarchy fuzzy system based on a unified model. First, a hierarchy fuzzy system with an increasing shape structure is established, namely, each basic hierarchy unit only has two physical input quantities collected from an industry production field. Through defining a uniform universe of discourse interval, the variation range of the actual physical input quantity is analyzed, the input quality is mapped uniformly on the defined interval, namely, the interval is used as the basic universe of discourse of the fuzzy system; each basic fuzzy unit adopts the same fuzzy reasoning way, namely, the same universe of discourse, the same fuzzy way and the uniform fuzzy reasoning rule, the fuzzy reasoning adopts the Mamdani composition arithmetic which is simple and convenient to calculate, based on which, a vacancy replacement processing mode is adopted for the unsure physical input quantity, the output weight sum of each layer of fuzzy basic unit is adopted for system output, and the feedback and adjusting for the system result is realized through an interval mapping adjusting way. The present invention solves the actual problems of the complexity of design and the real-time property of operation, thereby guaranteeing the practicability of the hierarchy fuzzy system.

Description

technical field [0001] The invention relates to a multi-input variable fuzzy reasoning model for industrial real-time requirements, in particular to a layered fuzzy system based on a unified model. Background technique [0002] In the actual industrial production, due to the complexity and uncertainty of the industrial production process, people have used the theory of intelligence to solve the problems in production. Fuzzy theory is an effective method to solve the problems of randomness and uncertainty. The conventional fuzzy model is planar, that is, the system usually has two or three input quantities, and these input quantities enter the model at the same time for fuzzy reasoning. Theoretically Although the conventional fuzzy model can also have more than three input quantities, because the number of fuzzy rules is exponentially related to the number of quantized fuzzy subsets, the more input quantities, the more the number of rules. Assuming that there are N fuzzy sub...

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Application Information

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IPC IPC(8): G05B13/02
Inventor 王杰朱晓东刘刚陈树伟刘艳红王东署
Owner ZHENGZHOU UNIV
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