IDENTIFICATION AND PREDICTIVE CONTROL OF A SIMULATED MOVING BED PROCESS

This paper is focused on the design of a Model Predictive Control (MPC) algorithm to control and optimize the methanol synthesis in a Simulated Moving Bed (SMB) reactor. First, the advantages that can be obtained when the process in carried out in this reactor configuration are summarized; then, the control algorithm is described. A simplified model based on Artificial Neural Networks (ANN) is used to calculate the control actions. The influence of the tuning parameters of the algorithm is studied by means of mathematical simulation, thus resulting in the best controller configuration. Finally, examples of the performance of the controlled system are provided, thus demonstrating the effectiveness of the proposed tool.

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Combination of multi-model predictive control and the wave theory for the control of simulated moving bed plants

Chemical Engineering Science ◽

10.1016/j.ces.2010.11.022 ◽

2011 ◽

Vol 66 (4) ◽

pp. 632-641 ◽

Cited By ~ 17

Author(s):

Carlos Vilas ◽

Alain Vande Wouwer

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Wave Theory ◽

Simulated Moving Bed ◽

Moving Bed

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Optimization-based predictive control of a simulated moving bed process using an identified model

Chemical Engineering Science ◽

10.1016/j.ces.2006.05.043 ◽

2006 ◽

Vol 61 (18) ◽

pp. 6165-6179 ◽

Cited By ~ 17

Author(s):

In-Hyoup Song ◽

Sang-Beom Lee ◽

Hyun-Ku Rhee ◽

Marco Mazzotti

Keyword(s):

Predictive Control ◽

Simulated Moving Bed ◽

Moving Bed

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Applicant hierarchical fuzzy controller for concentration control of simulated moving bed

Scientific Reports ◽

10.1038/s41598-021-97134-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Chaofan Xie ◽

Yang-jie Tang

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Pid Controller ◽

Fuzzy Controller ◽

Continuous Process ◽

Simulated Moving Bed ◽

Moving Bed ◽

Prediction And Control ◽

Precise Prediction ◽

And Control

AbstractSimulated moving bed (SMB) is a kind of continuous process which can increase the efficiency of adsorbents in the adsorbent bed. It contains several sectors of flow rate, the switching time of valves and many other possible influencing variables, moreover, these parameters are highly sensitive, so it is very difficult to achieve precise prediction and control. Model predictive control and PID controller are often used in industrial system. Model predictive control needs a lot of accurate industry experience data, and PID controller depends on the selection of control parameters. Therefore, SMB needs an intelligent controller to bypass those complex mechanisms and parameter adjustment processes. This paper we propose the hierarchical fuzzy controller fuzzy controller which is applied to the SMB system to observe the final concentration. Compared with the PID and MPC controller, it is found that the hierarchical fuzzy controller can control good without knowing the system parameters too accurately.

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