Nonlinear State Estimation and Model Predictive Control of Nitrogen Purification Columns

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• 作者：Shoujun Bian ; Michael A. Henson ; Paul Belanger ; and Lawrence Megan
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2005
• 出版时间：January 5, 2005
• 年：2005
• 卷：44
• 期：1
• 页码：153 - 167
• 全文大小：317K
• 年卷期：v.44,no.1(January 5, 2005)
• ISSN：1520-5045

文摘

Nitrogen purification columns are critical unit operations of air separation plants that producepurified gases for the chemical, steel, food processing, medical, and semiconductor industries.The need to operate these very high purity columns over a wide range of production rates inresponse to time-varying electrical costs motivates the development of nonlinear controlstrategies. We utilize a nonlinear wave model previously developed by our group to design anonlinear model predictive controller for a simulated nitrogen purification column. A firstprinciples model constructed in Aspen Dynamics (Aspen Technology) is used as a surrogate plantin the simulation studies. Estimates of the unmeasured wave position and key wave modelparameters are generated with an extended Kalman filter using a combination of compositionand temperature measurements strategically placed along the column. Several estimatorformulations are investigated to evaluate the effects of different measurement combinations.The estimator and predictive controller are combined through a state disturbance model thatprovides feedback and eliminates offset due to modeling errors. The controller manipulates thevapor nitrogen production rate to achieve the target nitrogen purity. The proposed controlstrategy is compared to a classical control system consisting of a ratio controller and aproportional-integral-derivative controller to analyze the potential benefits of nonlinear model-based control for this process.