{"title":"Applications of the Partial Fraction Decomposition to Pole Variation Rate for Root Locus Construction","authors":"Davide Tebaldi;Roberto Zanasi","doi":"10.1109/LCSYS.2024.3511995","DOIUrl":null,"url":null,"abstract":"The applications of the partial fraction decomposition in control and systems engineering are several. In this letter, we use the partial fraction decomposition to address the pole variation rate problem, namely to study the rate of variation of the system poles when the control parameter changes and when the system is subject to variations of its own parameters, which has led to the proposal of a new algorithm for the construction of the root locus. The new algorithm is proven to be much more efficient in terms of execution time than the dedicated MATLAB function, while providing the same output results.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"2925-2930"},"PeriodicalIF":2.4000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10778273","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Control Systems Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10778273/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The applications of the partial fraction decomposition in control and systems engineering are several. In this letter, we use the partial fraction decomposition to address the pole variation rate problem, namely to study the rate of variation of the system poles when the control parameter changes and when the system is subject to variations of its own parameters, which has led to the proposal of a new algorithm for the construction of the root locus. The new algorithm is proven to be much more efficient in terms of execution time than the dedicated MATLAB function, while providing the same output results.