Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Identification of Simulated Moving Bed Dynamic System by Neural Network

I-Chun Chen, Huang-Chu Huang, Chi-Yen Shen, and Rey-Chue Hwang

(Received December 13, 2019; Accepted September 8, 2020)

Keywords: system identification, SMB, neural network

This paper presents a study about the possibility of system identification for a simulated moving bed (SMB), which is an important step for developing a smart SMB automatic control mechanism with precise control capability. An SMB is a very complex and nonlinear system that is constructed from multiple columns in series and complex valve arrangements. All feed mixtures and solvents and the flow of desorbent are controlled by the columns and valve devices at a fixed switching time. Thus, if the operational behavior of an SMB system can be identified in advance, then the precise control of the system can be achieved easily. In this study, the neural network (NN) technique was used to identify an SMB system. From the experimental results shown, it was found that an NN is a very effective tool for SMB system identification.

Corresponding author: Rey-Chue Hwang




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