SCI和EI收录∣中国化工学会会刊

›› 2015, Vol. 23 ›› Issue (2): 398-411.DOI: 10.1016/j.cjche.2014.09.020

• 过程系统工程与过程安全 • 上一篇    下一篇

A novel interactive preferential evolutionary method for controller tuning in chemical processes

Chong Su, Hongguang Li   

  1. Beijing University of Chemical Technology, Beijing 100029, China
  • 收稿日期:2013-12-24 修回日期:2014-06-03 出版日期:2015-02-28 发布日期:2015-03-01
  • 通讯作者: Hongguang Li
  • 基金资助:
    Supported by the Fundamental Research Funds for the Central Universities (ZY1347 and YS1404).

A novel interactive preferential evolutionary method for controller tuning in chemical processes

Chong Su, Hongguang Li   

  1. Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2013-12-24 Revised:2014-06-03 Online:2015-02-28 Published:2015-03-01
  • Supported by:
    Supported by the Fundamental Research Funds for the Central Universities (ZY1347 and YS1404).

摘要: In response to many multi-attribute decision-making (MADM) problems involved in chemical processes such as controller tuning, which suffer human's subjective preferential nature in human-computer interactions, a novel affective computing and preferential evolutionary solution is proposed to adapt human-computer interaction mechanism. Based on the stimulating response mechanism, an improved affective computing model is introduced to quantify decision maker's preference in selections of interactive evolutionary computing. In addition, the mathematical relationship between affective space and decision maker's preferences is constructed. Subsequently, a human-computer interactive preferential evolutionary algorithm for MADM problems is proposed, which deals with attribute weights and optimal solutions based on preferential evolution metrics. To exemplify applications of the proposedmethods, some test functions and, emphatically, controller tuning issues associated with a chemical process are investigated, giving satisfactory results.

关键词: Preference, Affective computing, Interactive evolutionary computation, Multi-attribute decision-making, Controller tuning

Abstract: In response to many multi-attribute decision-making (MADM) problems involved in chemical processes such as controller tuning, which suffer human's subjective preferential nature in human-computer interactions, a novel affective computing and preferential evolutionary solution is proposed to adapt human-computer interaction mechanism. Based on the stimulating response mechanism, an improved affective computing model is introduced to quantify decision maker's preference in selections of interactive evolutionary computing. In addition, the mathematical relationship between affective space and decision maker's preferences is constructed. Subsequently, a human-computer interactive preferential evolutionary algorithm for MADM problems is proposed, which deals with attribute weights and optimal solutions based on preferential evolution metrics. To exemplify applications of the proposedmethods, some test functions and, emphatically, controller tuning issues associated with a chemical process are investigated, giving satisfactory results.

Key words: Preference, Affective computing, Interactive evolutionary computation, Multi-attribute decision-making, Controller tuning