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Certain studies on sample time for a predictive fuzzy logic controller through real time implementation of phenol-formaldehyde manufacturing

机译:通过实时实施苯酚甲醛生产来预测模糊逻辑控制器的采样时间的某些研究

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In polymer manufacturing industries, the automation and control of chemical process incorporating techniques of fuzzy control neural networks, and expert systems had lead to a more secured and stable operation. A sudden and unpredictable heat is often produced by the nonlinear exothermal reaction when phenol and formaldehyde are mixed together. Therefore, the polymerization process has to be controlled with a high level of precision in order to avoid temperature run-away. This paper proposes a design methodology for a sensor based process control system. The duration of ON and OFF time of certain relays are the parameters to be controlled in order to keep the exothermic reaction under control The universe of discourse for the output of the FLC system is the sample time that assigned to the relays where maximum time for heater or valve can be turned on before the next action is applied This paper discusses a detailed real time implementation of the exothermal process control using Matlab-fuzzy logic toolbox. An enhanced predictive FLC structure is developed and compared to a predictive FLC control structure. The obtained practical results thus ensure that the predictive FLC can be enhanced by modifying the rules and the membership Junctions of the universe of discourse, which is proved to be better in controlling the reaction temperature.
机译:在聚合物制造行业中,化学过程的自动化和控制结合了模糊控制神经网络技术和专家系统,从而使操作更加安全和稳定。当苯酚和甲醛混合在一起时,非​​线性的放热反应通常会产生突然而无法预测的热量。因此,为了避免温度失控,必须高度精确地控制聚合过程。本文提出了一种基于传感器的过程控制系统的设计方法。某些继电器的ON和OFF时间的持续时间是为了控制放热反应而要控制的参数。FLC系统输出的论述范围是分配给继电器的采样时间,其中加热器的最大时间或在执行下一个动作之前可以先打开阀门。本文讨论了使用Matlab模糊逻辑工具箱对放热过程控制进行实时详细控制的过程。开发了增强的预测FLC结构,并将其与预测FLC控制结构进行了比较。因此,获得的实际结果确保可以通过修改话语宇宙的规则和隶属结来增强预测性FLC,这被证明可以更好地控制反应温度。

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