{"title":"一种新的非线性电液伺服系统参数辨识方法","authors":"Pan Zhao, Shaoping Wang, Xin Li, Boya Zhang","doi":"10.1109/FPM.2011.6045824","DOIUrl":null,"url":null,"abstract":"This paper presents a parameter identification method with nonlinear ordinary differential equation (ODE) model for electro-hydraulic servo systems (EHSS) based on Matlab toolbox, in which the values of known parameters are fixed and the values of unknown parameters are identified. In order to avoid the problem of over-parameterization, this paper divides the identification into two parts, i.e. no-load identification (identification of the system without load) and with-load identification (identification of the system with load). To test the performance of this method, it is applied to a set of simulated data. Identification results demonstrate perfect correspondence between the data and the identified models.","PeriodicalId":241423,"journal":{"name":"Proceedings of 2011 International Conference on Fluid Power and Mechatronics","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A novel method of parameter identification of nonlinear electrohydraulic servo systems\",\"authors\":\"Pan Zhao, Shaoping Wang, Xin Li, Boya Zhang\",\"doi\":\"10.1109/FPM.2011.6045824\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a parameter identification method with nonlinear ordinary differential equation (ODE) model for electro-hydraulic servo systems (EHSS) based on Matlab toolbox, in which the values of known parameters are fixed and the values of unknown parameters are identified. In order to avoid the problem of over-parameterization, this paper divides the identification into two parts, i.e. no-load identification (identification of the system without load) and with-load identification (identification of the system with load). To test the performance of this method, it is applied to a set of simulated data. Identification results demonstrate perfect correspondence between the data and the identified models.\",\"PeriodicalId\":241423,\"journal\":{\"name\":\"Proceedings of 2011 International Conference on Fluid Power and Mechatronics\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2011 International Conference on Fluid Power and Mechatronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPM.2011.6045824\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2011 International Conference on Fluid Power and Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPM.2011.6045824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel method of parameter identification of nonlinear electrohydraulic servo systems
This paper presents a parameter identification method with nonlinear ordinary differential equation (ODE) model for electro-hydraulic servo systems (EHSS) based on Matlab toolbox, in which the values of known parameters are fixed and the values of unknown parameters are identified. In order to avoid the problem of over-parameterization, this paper divides the identification into two parts, i.e. no-load identification (identification of the system without load) and with-load identification (identification of the system with load). To test the performance of this method, it is applied to a set of simulated data. Identification results demonstrate perfect correspondence between the data and the identified models.