{"title":"Fractional order butterworth filter design using Artificial Bee colony algorithm","authors":"Atul Kumar Dwivedi, S. Bhatt, Subhojit Ghosh","doi":"10.1109/ISED.2017.8303938","DOIUrl":null,"url":null,"abstract":"Fractional order representation has been more effective in analyzing various physical systems more efficiently as compared to conventional integer order representation. Fractional order representation allows higher order integer systems to be replaced by small fractional order equivalent systems. In this paper, fractional order filters are designed using Swarm intelligence based evolutionary optimization algorithm. The designed filters have been compared with other state of the art evolutionary optimization techniques. In order to evaluate the order reduction by the proposed technique the designed filters are converted to equivalent higher order digital filter. The applicability of the designed filters for real time applications has been validated using TMS320F2812 DSP processor.","PeriodicalId":147019,"journal":{"name":"2017 7th International Symposium on Embedded Computing and System Design (ISED)","volume":"1965 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Symposium on Embedded Computing and System Design (ISED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISED.2017.8303938","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Fractional order representation has been more effective in analyzing various physical systems more efficiently as compared to conventional integer order representation. Fractional order representation allows higher order integer systems to be replaced by small fractional order equivalent systems. In this paper, fractional order filters are designed using Swarm intelligence based evolutionary optimization algorithm. The designed filters have been compared with other state of the art evolutionary optimization techniques. In order to evaluate the order reduction by the proposed technique the designed filters are converted to equivalent higher order digital filter. The applicability of the designed filters for real time applications has been validated using TMS320F2812 DSP processor.