{"title":"Modelling dynamic response of physical systems in Simulink","authors":"K. T. Smith, D. Rubin, M. Turner","doi":"10.1109/SAIBMEC.2018.8363187","DOIUrl":null,"url":null,"abstract":"The value of implementing mathematical models in Simulink is demonstrated through an overview of the challenges involved when determining the dynamic response of non-linear systems. This overview is demonstrated by using an example of the baroreceptor nerve (and its response to blood pressure changes) as a non-linear system which can be modelled and simulated in Simulink. The simulated results indicate that a comparison can be made to actual short-term experimental data and simulated data to validate the model. Thereafter, the simulated model can be tested using artificial long-term inputs which infer a non-linear system's dynamic response. This method would be valuable for any research or design where a non-linear physical system's dynamic response would be otherwise experimentally expensive or impossible.","PeriodicalId":165912,"journal":{"name":"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAIBMEC.2018.8363187","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
The value of implementing mathematical models in Simulink is demonstrated through an overview of the challenges involved when determining the dynamic response of non-linear systems. This overview is demonstrated by using an example of the baroreceptor nerve (and its response to blood pressure changes) as a non-linear system which can be modelled and simulated in Simulink. The simulated results indicate that a comparison can be made to actual short-term experimental data and simulated data to validate the model. Thereafter, the simulated model can be tested using artificial long-term inputs which infer a non-linear system's dynamic response. This method would be valuable for any research or design where a non-linear physical system's dynamic response would be otherwise experimentally expensive or impossible.