{"title":"Application of Stochastic Fractal Search in order reduction of large scale LTI systems","authors":"I. Khanam, G. Parmar","doi":"10.1109/COMPTELIX.2017.8003962","DOIUrl":null,"url":null,"abstract":"Order reduction of large scale single-input single-output (SISO) linear time invariant (LTI) systems using stochastic fractal search (SFS) algorithm has been presented. Stochastic Fractal Search (SFS) is a metahuristic algorithm growth using the concept of fractal. SFS employs the diffusion property observed in random fractals to explore the search space. Stochastic rules like; Gaussian walks are used to change the iteration process to generate random fractals. Here, for order reduction of LTI system, SFS Algorithm is used. Integral square error (ISE) in between the transient responses of original higher order and reduced order system has been taken as an objective function, which has been minimized. The step and frequency responses of both low and high order systems have also been compared along with the transient response's parameters. A comparative study of ISE with the other existing techniques in the literature has also been given in the tabular form to show the superiority of the algorithm.","PeriodicalId":6917,"journal":{"name":"2017 International Conference on Computer, Communications and Electronics (Comptelix)","volume":"18 1","pages":"190-194"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer, Communications and Electronics (Comptelix)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPTELIX.2017.8003962","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Order reduction of large scale single-input single-output (SISO) linear time invariant (LTI) systems using stochastic fractal search (SFS) algorithm has been presented. Stochastic Fractal Search (SFS) is a metahuristic algorithm growth using the concept of fractal. SFS employs the diffusion property observed in random fractals to explore the search space. Stochastic rules like; Gaussian walks are used to change the iteration process to generate random fractals. Here, for order reduction of LTI system, SFS Algorithm is used. Integral square error (ISE) in between the transient responses of original higher order and reduced order system has been taken as an objective function, which has been minimized. The step and frequency responses of both low and high order systems have also been compared along with the transient response's parameters. A comparative study of ISE with the other existing techniques in the literature has also been given in the tabular form to show the superiority of the algorithm.