模型不确定条件下预测控制经济性能评估的研究

林晓钟; 谢磊; 苏宏业

doi:10.3724/SP.J.1004.2013.01141

模型不确定条件下预测控制经济性能评估的研究

doi: 10.3724/SP.J.1004.2013.01141

1.
浙江大学智能与系统控制研究所工业控制技术国家重点实验室杭州 310027

基金项目:

国家自然科学基金(61134007,60904039),中央高校基本科研业务费专项基金资助

详细信息

通讯作者:
谢磊

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- 被引次数: 0
出版历程
- 收稿日期: 2012-05-15
- 修回日期: 2012-08-14
- 刊出日期: 2013-07-20

Economic Performance for Predictive Control Systems under Model Uncertainty

1.
State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems Control, Zhejiang University, Hangzhou 310027

Funds:

Supported by National Natural Science Foundation of China (61134007,60904039) and the Fundamental Resental Research Funds for the Central Universities

摘要

摘要: 为了解决在模型不确定条件下的预测控制系统经济性能评估分析的问题,本文通过基于二次锥规划的鲁棒线性规划的方法来描述模型不确定性对控制系统经济性能评估造成的影响,并采用约束调整与方差调整的策略来改善控制系统的经济性能. Shell公司提供的重油分馏塔典型案例实验证明该方法的有效性.
- 模型不确定性 /
- 经济性能评估 /
- 约束调整 /
- 方差调整 /
- 二次锥规划
Abstract: In order to solve the problem in evaluating economic performance for predictive control systems in the case of model uncertainty appropriately a robust linear programme method is proposed based on a second-order cone programme to describe the affect on economic performance assessment due to the model uncertainty. Then some constraint tuning and variability tuning are done to improve the economic performance. Simulation results of a typical control problem of a heavy oil fractionator proposed by Royal Dutch/Shell Group showed the effectivity of the proposed algorithm.
- Model uncertainty /
- economic performance assessment /
- constraint tuning /
- variability tuning /
- second-order cone programme

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参考文献(13)

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