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Abstract

This paper is devoted to the modeling and synthesis of an adaptive neuro-fuzzy control system for steam generator temperature. Temperature control systems play an important role in industry because accurate and stable control is a prerequisite for the efficient operation of steam systems. Traditional control methods based on mathematical models and fixed parameter controllers may have limitations in providing optimal performance and adapting to changing operating conditions. The paper proposes a synthesized system combining fuzzy logic and adaptation methods to achieve more accurate and stable temperature control. A detailed structural diagram of the system, modeling, and tuning methods are presented. The results of the study can be applied to improve the efficiency and reliability of temperature control in steam generators in various industries. The proposed control system has the potential for application in various industrial sectors where accurate and adaptive temperature control of steam generators is required. It can help to improve process efficiency and reduce energy costs.

First Page

48

Last Page

58

References

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