A novel intelligent ARX-Laguerre distillation column estimation technique
Автор: Farzin Piltan, Shahnaz TayebiHaghighi, Somayeh Jowkar, Hossein Rashidi Bod, Amirzubir Sahamijoo, Jeong-Seok Heo
Журнал: International Journal of Intelligent Systems and Applications @ijisa
Статья в выпуске: 4 vol.11, 2019 года.
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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 identification 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.
Distillation column, system identification, ARX modeling, intelligent nonlinear-ARX-Laguerre, ARX-Laguerre modeling
Короткий адрес: https://sciup.org/15016587
IDR: 15016587 | DOI: 10.5815/ijisa.2019.04.05
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