{"title":"模糊神经网络控制EHSS速度","authors":"S.A. Mohseni, M. Aliyari, M. Teshnehlab","doi":"10.1109/NAFIPS.2007.383803","DOIUrl":null,"url":null,"abstract":"In this paper a fuzzy neural network (FNN) is presented for velocity control of an electro hydraulic servo system (EHSS) in presence of flow nonlinearties and internal friction. The system contains several major nonlinearties that limit the ability of simple controllers in achieving satisfactory performance. These nonlinearties include: valve dead zones, valve flow saturation, and cylinder seal friction. The performances achievable by classical linear controllers, e.g. PD, are usually limited due to highly nonlinear behavior of the hydraulic dynamics. It is shown that the fuzzy neural controller, which is employed in this paper, can be successfully used to stabilize any chosen operating point of the system. The EBP (error back propagation) method is employed in FNN and the advantaged are mentioned. The approach can be further extended to the control of hydraulically driven manipulators. All derived results are validated by computer simulation of a nonlinear mathematical model of the system.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"EHSS Velocity Control by Fuzzy Neural Networks\",\"authors\":\"S.A. Mohseni, M. Aliyari, M. Teshnehlab\",\"doi\":\"10.1109/NAFIPS.2007.383803\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a fuzzy neural network (FNN) is presented for velocity control of an electro hydraulic servo system (EHSS) in presence of flow nonlinearties and internal friction. The system contains several major nonlinearties that limit the ability of simple controllers in achieving satisfactory performance. These nonlinearties include: valve dead zones, valve flow saturation, and cylinder seal friction. The performances achievable by classical linear controllers, e.g. PD, are usually limited due to highly nonlinear behavior of the hydraulic dynamics. It is shown that the fuzzy neural controller, which is employed in this paper, can be successfully used to stabilize any chosen operating point of the system. The EBP (error back propagation) method is employed in FNN and the advantaged are mentioned. The approach can be further extended to the control of hydraulically driven manipulators. All derived results are validated by computer simulation of a nonlinear mathematical model of the system.\",\"PeriodicalId\":292853,\"journal\":{\"name\":\"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2007.383803\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2007.383803","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper a fuzzy neural network (FNN) is presented for velocity control of an electro hydraulic servo system (EHSS) in presence of flow nonlinearties and internal friction. The system contains several major nonlinearties that limit the ability of simple controllers in achieving satisfactory performance. These nonlinearties include: valve dead zones, valve flow saturation, and cylinder seal friction. The performances achievable by classical linear controllers, e.g. PD, are usually limited due to highly nonlinear behavior of the hydraulic dynamics. It is shown that the fuzzy neural controller, which is employed in this paper, can be successfully used to stabilize any chosen operating point of the system. The EBP (error back propagation) method is employed in FNN and the advantaged are mentioned. The approach can be further extended to the control of hydraulically driven manipulators. All derived results are validated by computer simulation of a nonlinear mathematical model of the system.