Process Real-Time Optimization using Clonalg Algorithm

被引：0
|
作者：
Yang Zhong [1 ]
Chen Yang [1 ]
Chen Yuchen [2 ]
Shi Xuhua [1 ]
机构：
[1] Ningbo Univ, Coll Informat Sci & Engn, Ningbo 315211, Zhejiang, Peoples R China
[2] Ningbo Univ, Fac Architectural Civil Engn & Environm, Ningbo 315211, Zhejiang, Peoples R China
来源：
2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2015年
关键词：
real-time optimization; real-time evolution; Clonalg algorithm; EVOLUTION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Based on machine learning and immune mechanism, a useful framework for process real-time optimization is put forward in this paper. The proposed framework using real time evolutionary (RTE) approach with Clonalg algorithm (RTE-Clonalg) need not wait for the steady-state which is involved by the traditional Real-Time Optimization (RTO). RTE-Clonalg can adjust the set point continuously to approach the optimal points, so that the system can deal with the higher frequency disturbance, since the steady-state shouldn't be waited for to execute RTE system. The performance of the proposed method was successfully proved by Tennessee Eastman process.
引用
收藏
页码：743 / 748
页数：6
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