{"title":"基于差分进化优化算法的大规模线性动态SISO和MIMO系统缩减","authors":"G. Vasu, K. Santosh, G. Sandeep","doi":"10.1109/SCEECS.2012.6184732","DOIUrl":null,"url":null,"abstract":"In this paper, a computationally simple approach is proposed for order reduction of large scale system linear dynamic SISO and MIMO system using differential evolutionary (DE) optimization technique. The method is based on minimizing the integral square error (ISE) between the transient responses of original and reduced order models pertaining to step input. The reduction procedure is simple, efficient and computer oriented. Stability of the reduced order system is always assured in proposed method. The algorithm is illustrated with help of two numerical examples and results are compared with other well known reduction techniques to show its superiority.","PeriodicalId":372799,"journal":{"name":"2012 IEEE Students' Conference on Electrical, Electronics and Computer Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Reduction of large scale linear dynamic SISO and MIMO systems using differential evolution optimization algorithm\",\"authors\":\"G. Vasu, K. Santosh, G. Sandeep\",\"doi\":\"10.1109/SCEECS.2012.6184732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a computationally simple approach is proposed for order reduction of large scale system linear dynamic SISO and MIMO system using differential evolutionary (DE) optimization technique. The method is based on minimizing the integral square error (ISE) between the transient responses of original and reduced order models pertaining to step input. The reduction procedure is simple, efficient and computer oriented. Stability of the reduced order system is always assured in proposed method. The algorithm is illustrated with help of two numerical examples and results are compared with other well known reduction techniques to show its superiority.\",\"PeriodicalId\":372799,\"journal\":{\"name\":\"2012 IEEE Students' Conference on Electrical, Electronics and Computer Science\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Students' Conference on Electrical, Electronics and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCEECS.2012.6184732\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Students' Conference on Electrical, Electronics and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCEECS.2012.6184732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reduction of large scale linear dynamic SISO and MIMO systems using differential evolution optimization algorithm
In this paper, a computationally simple approach is proposed for order reduction of large scale system linear dynamic SISO and MIMO system using differential evolutionary (DE) optimization technique. The method is based on minimizing the integral square error (ISE) between the transient responses of original and reduced order models pertaining to step input. The reduction procedure is simple, efficient and computer oriented. Stability of the reduced order system is always assured in proposed method. The algorithm is illustrated with help of two numerical examples and results are compared with other well known reduction techniques to show its superiority.