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Controlling and modeling phases of distillation column using artificial neural networks

Mohammad M.Zarei, Jafar Sadeghi, Fariba Zarei


In this paper is described the choice of the control system design for a binary distillation column. The column has been formed dynamically. Using artificial neural networks (ANN) in system control design, the effects of disturbance on the column has been rejected to modeling ANN. These networks are used to model complex and non-linear processes and have the potential to solve some types of complex problems, where traditional methods wonÂ’t answer properly. Using dynamic simulation, the proper educational, testing and validation data for designing neural network is yielded. Modeling the system is done by multi layer perceptrons Levenberg-Marquardt algorithm. Finally, according to the error result values, acceptable errors for neural network are presented.


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索引于

  • 中国社会科学院
  • 谷歌学术
  • 打开 J 门
  • 中国知网(CNKI)
  • 引用因子
  • 宇宙IF
  • 米亚尔
  • 秘密搜索引擎实验室
  • 欧洲酒吧
  • 巴塞罗那大学
  • ICMJE

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