A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

doi:10.1016/S1004-9541(14)60057-4

Chinese Journal of Chemical Engineering ›› 2014, Vol. 22 ›› Issue (3): 318-329.DOI: 10.1016/S1004-9541(14)60057-4

• 过程系统工程与过程安全 • 上一篇下一篇

A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

杨国军, 李秀喜, 钱宇

School of Chemical Engineering, South China University of Technology, Guangzhou 510640, China

收稿日期:2013-03-23 修回日期:2013-05-23 出版日期:2014-03-28 发布日期:2014-03-05
通讯作者: QIAN Yu
基金资助:
Supported by the National Natural Science Foundation of China (21136003,21176089), the National Science &Technology Support Plan (2012BAK13B02), the National Major Basic Research Program (2014CB744306), the Natural Science Foundation Team Project of Guangdong Province (S2011030001366), and the Fundamental Research Funds for Central Universities (2013ZP0010).

A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

YANG Guojun, LI Xiuxi, QIAN Yu

School of Chemical Engineering, South China University of Technology, Guangzhou 510640, China

Received:2013-03-23 Revised:2013-05-23 Online:2014-03-28 Published:2014-03-05
Contact: QIAN Yu
Supported by:
Supported by the National Natural Science Foundation of China (21136003,21176089), the National Science &Technology Support Plan (2012BAK13B02), the National Major Basic Research Program (2014CB744306), the Natural Science Foundation Team Project of Guangdong Province (S2011030001366), and the Fundamental Research Funds for Central Universities (2013ZP0010).

摘要/Abstract

摘要： Nonlinear model predictive control (NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computation. To facilitate the implementation of NMPC in batch processes, we propose a real-time updated model predictive control method based on state estimation. The method includes two strategies: a multiple model building strategy and a real-time model updated strategy. The multiple model building strategy is to produce a series of simplified models to reduce the on-line computational complexity of NMPC. The real-time model updated strategy is to update the simplified models to keep the accuracy of the models describing dynamic process behavior. The method is validated with a typical batch reactor. Simulation studies show that the new method is efficient and robust with respect to model mismatch and changes in process parameters.

关键词: batch process, exothermic batch reactor, nonlinear model predictive control, state estimation, real-time model update

Abstract: Nonlinear model predictive control (NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computation. To facilitate the implementation of NMPC in batch processes, we propose a real-time updated model predictive control method based on state estimation. The method includes two strategies: a multiple model building strategy and a real-time model updated strategy. The multiple model building strategy is to produce a series of simplified models to reduce the on-line computational complexity of NMPC. The real-time model updated strategy is to update the simplified models to keep the accuracy of the models describing dynamic process behavior. The method is validated with a typical batch reactor. Simulation studies show that the new method is efficient and robust with respect to model mismatch and changes in process parameters.

Key words: batch process, exothermic batch reactor, nonlinear model predictive control, state estimation, real-time model update

杨国军, 李秀喜, 钱宇. A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation[J]. Chinese Journal of Chemical Engineering, 2014, 22(3): 318-329.

YANG Guojun, LI Xiuxi, QIAN Yu. A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation[J]. Chin.J.Chem.Eng., 2014, 22(3): 318-329.

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A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

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