Jeong-Seok Heo

Work place: Control and Robotic Lab, IRAN SSP Research and Development Center, Shiraz, Iran



Research Interests:


Jeong-Seok Heo is currently a professor with the Department of IT convergence and also president of Ulsan College.

Author Articles
A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

By Farzin Piltan Shahnaz TayebiHaghighi Somayeh Jowkar Hossein Rashidi Bod Amirzubir Sahamijoo Jeong-Seok Heo

DOI:, Pub. Date: 8 Apr. 2019

In practical applications, modeling of real systems with unknown parameters such as distillation columns are typically complex. To address issues with distillation column estimation, the system is identified by a proposed intelligent, auto-regressive, exogenous-Laguerre (AI-ARX-Laguerre) technique. In this method, an intelligent technique is introduced for data-driven identiļ¬cation of the distillation column. The Laguerre method is used for the removal of input/output noise and decreases the system complexity. The fuzzy logic method is proposed to reduce the system’s estimation error and to accurately optimize the ARX-Laguerre parameters. The proposed method outperforms the ARX and ARX-Laguerre technique by achieving average estimation accuracy improvements of 16% and 9%, respectively.

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