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Improving the Paper Mill Head Box Consistency Control using Neuro-Fuzzy Technique

机译:采用神经模糊技术改善造纸厂头箱一致性控制

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The paper mills are one of the main industries on which the economy of India is based. The paper production process is very complex and comprised of several stages. One of them is the head box which is the key sub process of this entire system. It distributes the stock uniformly over the wire section of the paper mill. The automatic control system design is the focus of this paper. The considered process is very challenging for control system design due the presence of dead time which makes the system unstable. So, a very popular technique, IMC (internal model control), is attempted. Its performance is analyzed. Also, a modern approach, ANFIS (adaptive neuro fuzzy inference system) is adopted for the control system design for the same process. Finally, the control performance of both the approaches has been compared. For simulations, MATLAB is used in this work.
机译:造纸厂是印度经济为基础的主要产业之一。 纸生产过程非常复杂,包括几个阶段。 其中一个是头盒,这是整个系统的关键子过程。 它在造纸厂的电线段中均匀地分配股票。 自动控制系统设计是本文的重点。 考虑过程对于控制系统设计非常具有挑战性,因为存在死区时间,这使得系统不稳定。 因此,尝试了一种非常流行的技术,IMC(内部模型控制)。 分析了其性能。 此外,一种现代方法,ANFIS(自适应神经模糊推理系统)是用于相同过程的控制系统设计。 最后,已经比较了这两种方法的控制性能。 对于模拟,MATLAB在这项工作中使用。

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