{"title":"Automatic Transfer Function Improvement based on Genetic Algorithm","authors":"Nattapong Paenoi, S. Sitjongsataporn","doi":"10.1109/ICEAST52143.2021.9426275","DOIUrl":null,"url":null,"abstract":"This paper presents the automatic transfer function improvement based on the genetic algorithm for searching the optimal transfer function. A traditional genetic algorithm is modified to perform the searching process. The proposed chromosome design is presented in the form of 15-bit supported the resistance and inductance. Transfer function is used to design and control the systems. The optimal fitness function is used for the objective function of system to optimize the transfer function. Experiment results show that the second order of automatic transfer function performed by the genetic algorithm can achieve more accuracy than the traditional first order transfer function process. By the process improvement using the genetic algorithm, the time is used for searching transfer function with the chromosome design under the optimal fitness function by the genetic algorithm is approximately 13.35 seconds.","PeriodicalId":416531,"journal":{"name":"2021 7th International Conference on Engineering, Applied Sciences and Technology (ICEAST)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 7th International Conference on Engineering, Applied Sciences and Technology (ICEAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEAST52143.2021.9426275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents the automatic transfer function improvement based on the genetic algorithm for searching the optimal transfer function. A traditional genetic algorithm is modified to perform the searching process. The proposed chromosome design is presented in the form of 15-bit supported the resistance and inductance. Transfer function is used to design and control the systems. The optimal fitness function is used for the objective function of system to optimize the transfer function. Experiment results show that the second order of automatic transfer function performed by the genetic algorithm can achieve more accuracy than the traditional first order transfer function process. By the process improvement using the genetic algorithm, the time is used for searching transfer function with the chromosome design under the optimal fitness function by the genetic algorithm is approximately 13.35 seconds.