{"title":"一种改进的两轮自平衡车辆状态确定计算模型","authors":"Sufeng Wang, Hongyi Lu, Fangyong Hou","doi":"10.1109/CISP.2015.7408098","DOIUrl":null,"url":null,"abstract":"Owing to the estimating accuracy of state variable for a two-wheeled self-balancing vehicle is not high in a transient status, this paper presents an improved computing model based on a simplified force model of a two-wheeled self-balancing vehicle. Experimental results show that the improved computing model reduces the estimating error of state variable for a two-wheeled self-balancing vehicle in a transient status.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An improved computing model for a two-wheeled self-balancing vehicle's state determination\",\"authors\":\"Sufeng Wang, Hongyi Lu, Fangyong Hou\",\"doi\":\"10.1109/CISP.2015.7408098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Owing to the estimating accuracy of state variable for a two-wheeled self-balancing vehicle is not high in a transient status, this paper presents an improved computing model based on a simplified force model of a two-wheeled self-balancing vehicle. Experimental results show that the improved computing model reduces the estimating error of state variable for a two-wheeled self-balancing vehicle in a transient status.\",\"PeriodicalId\":167631,\"journal\":{\"name\":\"2015 8th International Congress on Image and Signal Processing (CISP)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 8th International Congress on Image and Signal Processing (CISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2015.7408098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Congress on Image and Signal Processing (CISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2015.7408098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved computing model for a two-wheeled self-balancing vehicle's state determination
Owing to the estimating accuracy of state variable for a two-wheeled self-balancing vehicle is not high in a transient status, this paper presents an improved computing model based on a simplified force model of a two-wheeled self-balancing vehicle. Experimental results show that the improved computing model reduces the estimating error of state variable for a two-wheeled self-balancing vehicle in a transient status.