scholarly journals System identification via nuclear norm regularization for simulated moving bed processes from incomplete data sets

2009 ◽  
Author(s):  
Cristian Grossmann ◽  
Colin N. Jones ◽  
Manfred Morari
Keyword(s):  
System Identification ◽  
Incomplete Data ◽  
Nuclear Norm ◽  
Simulated Moving Bed ◽  
Data Sets ◽  
Moving Bed ◽  
Nuclear Norm Regularization

scholarly journals Model Predictive Control Method of Simulated Moving Bed Chromatographic Separation Process Based on Subspace System Identification

2019 ◽  
Vol 2019 ◽  
pp. 1-24 ◽  
Author(s):  
Zhen Yan ◽  
Jie-Sheng Wang ◽  
Shao-Yan Wang ◽  
Shou-Jiang Li ◽  
Dan Wang ◽  
...  
Keyword(s):  
System Identification ◽  
State Space ◽  
Predictive Control ◽  
Chromatographic Separation ◽  
Control Method ◽  
Separation Process ◽  
Simulated Moving Bed ◽  
Moving Bed ◽  
Separation Technology ◽  
Subspace System Identification

Simulated moving bed (SMB) chromatographic separation is a new type of separation technology based on traditional fixed bed adsorption operation and true moving bed (TMB) chromatographic separation technology, which includes inlet-outlet liquid, liquid circulation, and feed liquid separation. The input-output data matrices were constructed based on SMB chromatographic separation process data. The SMB chromatographic separation process was modeled by utilizing two subspace system identification algorithms: multivariable output-error state-space (MOESP) identification algorithm and numerical algorithms for subspace state-space system identification (N4SID), so as to obtain the 3rd-order and 4th-order state-space yield models of the SMB chromatographic separation process, respectively. The model predictive control method based on the established state-space models is used in the SMB chromatographic separation process. The influence of different control indicators on the predictive control system response performance is discussed. The output response curves of the yield models were obtained by changing the related parameters so that the yield model parameters are optimized set meanwhile. Finally, the simulation results showed that the yield models are successfully controlled based on the each control period and given yield range.

A Reliability-Based Approach to Assess Fatigue Behaviour Based on Small Incomplete Data Sets

2008 ◽  
Vol 44-46 ◽  
pp. 871-878 ◽  
Author(s):  
Chu Yang Luo ◽  
Jun Jiang Xiong ◽  
R.A. Shenoi
Keyword(s):  
Incomplete Data ◽  
Standard Procedure ◽  
Fatigue Behaviour ◽  
Fatigue Tests ◽  
Small Sample ◽  
Data Sets ◽  
Safe Life ◽  
A New Technique ◽  
And Performance

This paper outlines a new technique to address the paucity of data in determining fatigue life and performance based on reliability concepts. Two new randomized models are presented for estimating the safe life and pS-N curve, by using the standard procedure for statistical analysis and dealing with small sample numbers of incomplete data. The confidence level formulations for the safe and p-S-N curve are also given. The concepts are then applied for the determination of the safe life and p-S-N curve. Two sets of fatigue tests for the safe life and p-S-N curve are conducted to validate the presented method, demonstrating the practical use of the proposed technique.

Design of a gas phase simulated moving bed for propane/propylene separation

2009 ◽  
Vol 64 (6) ◽  
pp. 1336-1357 ◽  
Author(s):  
Pedro Sá Gomes ◽  
Nabil Lamia ◽  
Alírio E. Rodrigues
Keyword(s):  
Gas Phase ◽  
Simulated Moving Bed ◽  
Moving Bed
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