Wang Bin1,Wang Sun'an1,Du Haifeng2
(1.School of Mechanical Engineering,Xi'an Jiaotong University,Xi'an 710049,China;2.Key Laboratory of Radar Signal Processing,Xidian University,Xi'an 710071,China)
Abstract:To solve the problem of the diverse control requirements and turning the control parameters in the modern complex industrial process,an approach for parameter optimization was proposed.In this approach,fuzzy evaluating approach was used to improve the simple genetic algorithms(SGA),and a fuzzy fitness function was designed to divide those control requirements into many evaluating factors of control result with different weights. The fitness of the individual shows the approximate degree of control requirements and the result controlled by individual(i.e. control parameters). The approach was used to optimize the control parameters of temperature controller in tower type fermenter. Experiments show that control indices, such as control error,the stableness of temperature change, energy consumption,and the frequency of electromagnetic value,are improved and this approach can successfully optimize the parameters in complex industrial process.
Keywords:complex industrial process;fuzzy genetic algorithms;parameter optimization