Adaptive generic model control scheme for an optimized external heat integrated air separation column using unscented kalman filter

被引:0
|
作者
Hamid, Hamedalneel Babiker Aboh [1 ]
Liu, Xinggao [1 ]
机构
[1] Zhejiang Univ, Coll Control Sci & Engn, State Key Lab Ind Control Technol, NG Platform, Hangzhou 310027, Peoples R China
基金
中国国家自然科学基金;
关键词
External heat-integrated air separation column; Adaptive generic model control; Decoupled ARX model; Parameters estimation; Unscented Kalman filter; PREDICTIVE CONTROL; STATE ESTIMATION; PARAMETER-ESTIMATION; DISTILLATION; INTENSIFICATION; DYNAMICS;
D O I
10.1016/j.cep.2024.109956
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
An External Heat-Integrated Air Separation Column (E-HIASC) process is a promising air separation technology. This study focuses on the operational stability of the optimized E-HIASC process for separating nitrogen, oxygen, and argon mixtures. The operation stability of process is achieved through an Adaptive Generic Model Control (AGMC) scheme which is designed by incorporating the identified E-HIASC state-space dynamic model into the controller algorithm. The controller synthesizes the Generic Model Control (GMC) algorithm, decoupled ARX model, and Unscented Kalman Filter (UKF) algorithm to enable the auto-regression and exogenous (ARX) for model identification and the UKF algorithm to estimate time-varying parameters and compute unmeasured EHIASC state parameters required in the GMC algorithm. A Generic Model Control (GMC) and Multivariable PID (M-PID) control schemes were also designed for benchmarking study. Simulation results show that an AGMC scheme performs better than the GMC and M-PID schemes in tracking the product concentration set point and disturbances rejection.
引用
收藏
页数:18
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