{"title":"非线性倒立摆系统的人工神经网络辨识","authors":"Pooja Gautam","doi":"10.1109/ICRAIE.2016.7939522","DOIUrl":null,"url":null,"abstract":"System identification is the process of developing a mathematical model of a system using input and output knowledge of system. Identification of nonlinear system is well known problem due to its unpredictability and complexity. The nonlinear system for identification is Inverted Pendulum in this work which is well known benchmark system in control system theory due to it's highly nonlinear and unstable characteristics. In this work Lagrangian approach has been used for system dynamic modelling. Artificial neural network is utilized for model identification.","PeriodicalId":400935,"journal":{"name":"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"System identification of nonlinear Inverted Pendulum using artificial neural network\",\"authors\":\"Pooja Gautam\",\"doi\":\"10.1109/ICRAIE.2016.7939522\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"System identification is the process of developing a mathematical model of a system using input and output knowledge of system. Identification of nonlinear system is well known problem due to its unpredictability and complexity. The nonlinear system for identification is Inverted Pendulum in this work which is well known benchmark system in control system theory due to it's highly nonlinear and unstable characteristics. In this work Lagrangian approach has been used for system dynamic modelling. Artificial neural network is utilized for model identification.\",\"PeriodicalId\":400935,\"journal\":{\"name\":\"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAIE.2016.7939522\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAIE.2016.7939522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System identification of nonlinear Inverted Pendulum using artificial neural network
System identification is the process of developing a mathematical model of a system using input and output knowledge of system. Identification of nonlinear system is well known problem due to its unpredictability and complexity. The nonlinear system for identification is Inverted Pendulum in this work which is well known benchmark system in control system theory due to it's highly nonlinear and unstable characteristics. In this work Lagrangian approach has been used for system dynamic modelling. Artificial neural network is utilized for model identification.