Formation of the Knowledge Base on the basis of Modeling the Technological Process with the Use of Fuzzy Logic

Author Name(s): Larisa A. Simonova, Ildar R. Davletshin
Author Email: lasimonova@mail.ru

Abstract

This article is devoted to the formation of a knowledge base of an intellectual add-on for technological process control systems based on modeling using fuzzy logic and a use-case system. The intelligent add-on is a multi-agent system that includes the agents of a different nature. This article focuses on agents working on fuzzy logic. The knowledge base is part of an intelligent control system and, in relation to production conditions, consists of a set of production rules that describe the dependence of the main indicators of the technological process. The study identified the main parameters of the melting process, as one of the processes that determine the quality of the finished product. A review of sources describing the production technology is carried out and rules are highlighted. Linguistic variables are defined and ranges of values in which they change are defined. The stages of obtaining a solution using fuzzy logic are described. A mathematical model has been created that is suitable for choosing the optimal process conditions and for integration into an intelligent superstructure as one of the components. The structure of the precedent is described, the algorithm is briefly described in the steps of selecting precedents, adding new precedents to the database.

Introduction

In modern conditions, the leading manufacturers of heat-insulating materials use automatic production lines, on which control tasks are carried out mainly with the help of SCADA-systems, however, there are still tasks that must be solved by a person. One of the further ways of developing automated production systems is the use of artificial intelligence and the creation of an intelligent add-on based on a multi-agent system [1] consisting of a coordinator agent and agents working on fuzzy logic [2] or neural networks. The advantage of multi-component systems is the absence of restrictions imposed on the nature of an agent. It can be a software module, electronic or physical mechanism. This feature allows you to combine different methods of emulating artificial intelligence when creating an intelligent add-on for a control system. Such an add-on allows improving existing management systems to address management issues in emergency situations.

Conclusion

The article lists the main indicators of the melting process, as one of the processes that determine the quality of the finished product. Linguistic variables are defined and ranges of values in which they change are defined. The stages of obtaining a solution using fuzzy logic are described. The use of linguistic variables, fuzzy logic rules, approximate reasoning allows you to bring the expert’s experience into the management of technological processes.

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