{"title":"倒立摆混合控制器","authors":"Y. Singh, M. Bhatotia, R. Mitra","doi":"10.1109/APCET.2012.6302042","DOIUrl":null,"url":null,"abstract":"Inverted pendulum system is a nonlinear multivariable system which is inherently unstable. It requires designing of a hybrid controller which can adapt in different disturbance conditions and work appreciably well when compared to conventional controllers. In this paper, a hybrid controller for inverted pendulum is designed. Initially Fuzzy and LQR controllers for inverted pendulum are designed, then data are collected from these controllers, which then are used to train Adaptive neuro-fuzzy inference system (ANFIS). This hybrid controller has advantages of Fuzzy, LQR controllers and of neural networks; so it gives better performance.","PeriodicalId":184844,"journal":{"name":"2012 International Conference on Advances in Power Conversion and Energy Technologies (APCET)","volume":"60 33","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Hybrid controller for inverted pendulum\",\"authors\":\"Y. Singh, M. Bhatotia, R. Mitra\",\"doi\":\"10.1109/APCET.2012.6302042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Inverted pendulum system is a nonlinear multivariable system which is inherently unstable. It requires designing of a hybrid controller which can adapt in different disturbance conditions and work appreciably well when compared to conventional controllers. In this paper, a hybrid controller for inverted pendulum is designed. Initially Fuzzy and LQR controllers for inverted pendulum are designed, then data are collected from these controllers, which then are used to train Adaptive neuro-fuzzy inference system (ANFIS). This hybrid controller has advantages of Fuzzy, LQR controllers and of neural networks; so it gives better performance.\",\"PeriodicalId\":184844,\"journal\":{\"name\":\"2012 International Conference on Advances in Power Conversion and Energy Technologies (APCET)\",\"volume\":\"60 33\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Advances in Power Conversion and Energy Technologies (APCET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCET.2012.6302042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Advances in Power Conversion and Energy Technologies (APCET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCET.2012.6302042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inverted pendulum system is a nonlinear multivariable system which is inherently unstable. It requires designing of a hybrid controller which can adapt in different disturbance conditions and work appreciably well when compared to conventional controllers. In this paper, a hybrid controller for inverted pendulum is designed. Initially Fuzzy and LQR controllers for inverted pendulum are designed, then data are collected from these controllers, which then are used to train Adaptive neuro-fuzzy inference system (ANFIS). This hybrid controller has advantages of Fuzzy, LQR controllers and of neural networks; so it gives better performance.