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Synthesis of the Adaptive-fuzzy System Regulating the Temperature of Overheated Steam in Heat-electric Objects

机译:用于调节热电物体过热蒸汽温度的自适应模糊系统的合成

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The article discusses the results of developing an algorithm for calculating the parameters of an adaptive controller when controlling the temperature of superheated steam. The presented control algorithm uses artificial neural networks. The purpose of this scientific work is to develop adaptive control capable of operating under unknown limited external disturbances with varying parameters of the thermoelectric boiler over time. Research methods are based on the provisions of modern areas of control theory, such as adaptive management and identification. Mathematical models are constructed by the analytical method using equations that describe the physical properties of the object. The methodology of creating a temperature control system for a superheater operating under conditions of a priori uncertainty is presented. It is shown that such control systems belong to adaptive systems capable of controlling an object with significant and previously unknown object parameters. It is proposed to use an artificial neuron as an adaptive part of a control system or their combination - artificial neural networks.
机译:本文讨论了在控制超热蒸汽温度时计算用于计算自适应控制器参数的算法的结果。呈现的控制算法使用人工神经网络。该科学工作的目的是开发能够在能够在未知的有限外部干扰下运行的自适应控制,随着时间的推移,热电锅炉的变化参数。研究方法基于现代控制理论的规定,如适应性管理和识别。使用描述物体属性的等式的分析方法构造数学模型。介绍了在经过先验不确定性的条件下运行的过热器的温度控制系统的方法。结果表明,这种控制系统属于能够控制具有重要和先前未知的对象参数的对象的自适应系统。建议使用人工神经元作为控制系统的自适应部分或其组合的人工神经网络。

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