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结合BFO及CBR的层流冷却水量优化设定方法
Alternative TitleOptimization setting control based on bacterial foraging optimization and case-based reasoning for laminar cooling water consumption
片锦香; 朱云龙; 刘金鑫; 柴天佑
Department信息服务与智能控制技术研究室
Source Publication仪器仪表学报
ISSN0254-3087
2015
Volume36Issue:3Pages:615-622
Indexed ByEI ; CSCD
EI Accession number20151800796994
CSCD IDCSCD:5390882
Contribution Rank1
Funding Organization国家自然科学基金(61174164,61440004)资助项目
Abstract层流冷却过程控制目标是保证带钢卷取温度进入目标范围内并尽量提高精度以保证带钢质量,其本质是目标优化问题。同时,层流冷却过程处于频繁变化操作工况的动态环境之下,现有控制方法很难实现有效的实时控制。本文针对现有层流冷却过程控制方法很少引入优化思想这一问题,提出基于改进菌群优化算法(BFO)的层流冷却过程冷却水量优化设定方法。并针对动态变化工况,引入案例推理(CBR)机制,提出离线优化——在线推理双层结构的动态优化设定控制结构。基于实际运行数据的实验结果说明,本文提出的方法能够有效搜索冷却水量的优化设定值,而且在变更带钢规格的变化工况条件下,能够及时调整冷却水量的设定值,最终使带钢卷取温度进入目标范围内。
Other AbstractThe function of laminar cooling control system is to control the strip coiling temperature into the allowed range, and the closer to the target temperature, the better strip quality is. Essentially, this is a target optimization problem. Laminar cooling operating condition is always varying and the process is in the dynamic environment, which is leading the difficulty of effective real-time control. Aiming at no optimization in the laminar cooling control methods, this paper proposed optimization setting control method of cooling water consumption, by introducing the improved bacterial foraging optimization (BFO). On the other hand, aiming at the dynamic operating condition, two layers structure of dynamic optimization setting is proposed with the mode of offline optimization and online reasoning, where case-based reasoning (CBR) is applied. The simulation results with industrial operating data showed the effectiveness in searching optimized cooling water consumption. Moreover, in the condition of varying working condition, the proposed method has the ability to adjust the water consumption setting value in time. As a result, the strip coiling temperature is controlled in the target range.
Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/16156
Collection信息服务与智能控制技术研究室
Affiliation1.中国科学院沈阳自动化研究所信息服务与智能控制研究室
2.沈阳建筑大学信息与控制工程学院
3.东北大学流程工业综合自动化国家重点实验室
Recommended Citation
GB/T 7714
片锦香,朱云龙,刘金鑫,等. 结合BFO及CBR的层流冷却水量优化设定方法[J]. 仪器仪表学报,2015,36(3):615-622.
APA 片锦香,朱云龙,刘金鑫,&柴天佑.(2015).结合BFO及CBR的层流冷却水量优化设定方法.仪器仪表学报,36(3),615-622.
MLA 片锦香,et al."结合BFO及CBR的层流冷却水量优化设定方法".仪器仪表学报 36.3(2015):615-622.
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