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

页码：743 / 748

页数：6

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