{"title":"自主自行车运动稳定模型预测控制设计方法","authors":"Omar Ai-Buraiki, M. B. Thabit","doi":"10.1109/MED.2014.6961401","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a model predictive control (MPC) approach for controlling the autonomous bicycle kinematics to stabilize the bicycle steer and roll angles. The dynamical model is the so-called `Whipples Bicycle Model', where the roll (lean) angle and the steer angle of the bicycle are the two outputs of the model and the torques across the roll and steer angle as the two control variables. The autonomous bicycle was tested for varying velocities.","PeriodicalId":127957,"journal":{"name":"22nd Mediterranean Conference on Control and Automation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Model predictive control design approach for autonomous bicycle kinematics stabilization\",\"authors\":\"Omar Ai-Buraiki, M. B. Thabit\",\"doi\":\"10.1109/MED.2014.6961401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a model predictive control (MPC) approach for controlling the autonomous bicycle kinematics to stabilize the bicycle steer and roll angles. The dynamical model is the so-called `Whipples Bicycle Model', where the roll (lean) angle and the steer angle of the bicycle are the two outputs of the model and the torques across the roll and steer angle as the two control variables. The autonomous bicycle was tested for varying velocities.\",\"PeriodicalId\":127957,\"journal\":{\"name\":\"22nd Mediterranean Conference on Control and Automation\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd Mediterranean Conference on Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MED.2014.6961401\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd Mediterranean Conference on Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MED.2014.6961401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model predictive control design approach for autonomous bicycle kinematics stabilization
In this paper, we propose a model predictive control (MPC) approach for controlling the autonomous bicycle kinematics to stabilize the bicycle steer and roll angles. The dynamical model is the so-called `Whipples Bicycle Model', where the roll (lean) angle and the steer angle of the bicycle are the two outputs of the model and the torques across the roll and steer angle as the two control variables. The autonomous bicycle was tested for varying velocities.