| 一类连续/间歇过程的迭代学习模型预测控制 |
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| 引用本文： | 周猛飞,王树青,金晓明,张泉灵.一类连续/间歇过程的迭代学习模型预测控制[J].中国化学工程学报,2009,17(6):976-982. |
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| 作者姓名： | 周猛飞 王树青 金晓明 张泉灵 |
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| 作者单位： | State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China |
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| 基金项目： | Supported by the National Creative Research Groups Science Foundation of China (60721062);the National High Technology Research and Development Program of China (2007AA04Z162) |
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| 摘 要： | An iterative learning model predictive control (ILMPC) technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control (ILC) handling repetitive signal and the flexibility of model predictive control (MPC). By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial appli-cation show that the proposed ILMPC method is effective for a class of continuous/batch processes.
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| 关 键 词： | continuous/batch process model predictive control event monitoring iterative learning soft constraint |
| 收稿时间： | 2009-3-12 |
| 修稿时间： | 2009-10-12
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Iterative Learning Model Predictive Control for a Class of Continuous/Batch Processes |
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| ZHOU Mengfei,WANG Shuqing,JIN Xiaoming,ZHANG Quanling.Iterative Learning Model Predictive Control for a Class of Continuous/Batch Processes[J].Chinese Journal of Chemical Engineering,2009,17(6):976-982. |
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| Authors: | ZHOU Mengfei WANG Shuqing JIN Xiaoming ZHANG Quanling |
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| Affiliation: | State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China |
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| Abstract: | An iterative learning model predictive control (ILMPC) technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control (ILC) handling repetitive signal and the flexibility of model predictive control (MPC). By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial appli-cation show that the proposed ILMPC method is effective for a class of continuous/batch processes. |
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| Keywords: | continuous/batch process model predictive control event monitoring iterative learning soft constraint |
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