基于历史目标函数基准的数据驱动子空间预测控制系统的性能监控

王陆; 李柠; 李少远

doi:10.3724/SP.J.1004.2013.00542

基于历史目标函数基准的数据驱动子空间预测控制系统的性能监控

doi: 10.3724/SP.J.1004.2013.00542

1.
上海交通大学自动化系系统控制与信息处理教育部重点实验室上海 200240

详细信息

通讯作者:
李柠

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出版历程
- 收稿日期: 2012-05-15
- 修回日期: 2013-03-27
- 刊出日期: 2013-05-20

Performance Monitoring of the Data-driven Subspace Predictive Control Systems Based on Historical Objective Function Benchmark

1.
Department of Automation, Shanghai Jiao Tong University, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China

摘要

摘要: 采用历史目标函数基准对数据驱动的子空间预测控制系统进行性能监控, 提出了一种新的历史数据集的选取算法, 该算法克服了以往历史数据集只能依赖经验选取的不足, 不仅可以由用户根据实际控制需求定义性能指标, 而且提高了监控的灵敏度与准确度. 通过Wood-Berry精馏塔的仿真验证了所提算法的有效性.
- 数据驱动, 子空间辨识, 模型预测控制, 性能监控, 历史目标函数基准
Abstract: In this paper, a historical objective function benchmark is proposed to monitor the performance of data-driven subspace predictive control systems. A new criterion for selection of the historical data set can be used to monitor the controller's performance, instead of using traditional methods based on prior knowledge. Under this monitoring framework, users can define their own index based on different demands and can also obtain the historical benchmark with a better sensitivity. Finally, a distillation column simulation example is used to illustrate the validity of the proposed algorithms.
- Data-driven, subspace identification, model predictive control, performance monitoring, historical objective function benchmark

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参考文献(1)

[1]

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