SCI和EI收录∣中国化工学会会刊

›› 2011, Vol. 19 ›› Issue (2): 299-307.

• PEOCESS SYSTEMS ENGINEERING • Previous Articles     Next Articles

A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering

YANG Chuanxin, YAN Xuefeng   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2010-05-05 Revised:2010-10-29 Online:2011-04-28 Published:2011-04-28
  • Supported by:
    Supported by the National Natural Science Foundation of China(20776042);the National High Technology Research and Development Program of China(2007AA04Z164);the Doctoral Fund of Ministry of Education of China(20090074110005);the Program for New Century Excellent Talents in University(NCET-09-0346);the"Shu Guang"Project(095G29);Shanghai Leading Academic Discipline Project(B504)

A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering

杨传鑫, 颜学峰   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • 通讯作者: YAN Xuefeng,E-mail:xfyan@ecust.edu.cn
  • 基金资助:
    Supported by the National Natural Science Foundation of China(20776042);the National High Technology Research and Development Program of China(2007AA04Z164);the Doctoral Fund of Ministry of Education of China(20090074110005);the Program for New Century Excellent Talents in University(NCET-09-0346);the"Shu Guang"Project(095G29);Shanghai Leading Academic Discipline Project(B504)

Abstract: Considering that the performance of a genetic algorithm (GA) is affected by many factors and their relationships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm (FAGA) combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex problems.In FAGA,immune theory is used to improve the performance of selection operation.And,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.The experiments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy GAs.Finally,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.

Key words: fuzzy logic controller, genetic algorithm, artificial immune system, reaction kinetics model

摘要: Considering that the performance of a genetic algorithm (GA) is affected by many factors and their relationships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm (FAGA) combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex problems.In FAGA,immune theory is used to improve the performance of selection operation.And,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.The experiments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy GAs.Finally,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.

关键词: fuzzy logic controller, genetic algorithm, artificial immune system, reaction kinetics model