{"title":"自主导航的观察者控制方案:四旋翼飞行器的飞行试验验证","authors":"L. E. Munoz, P. Castillo, P. Garcia","doi":"10.1109/ICUAS.2013.6564762","DOIUrl":null,"url":null,"abstract":"We present in this paper an improvement of a nonlinear control algorithm based on the Lyapunov analysis and the saturation functions, to realize autonomous navigation of a quadrotor vehicle. The algorithm is analyzed and the convergence of the states is ameliorated, in addition, the stability analysis in closed-loop system is proved with these new conditions. In order to locate the aerial vehicle a new position estimation algorithm is developed using the dead-reckoning technique with the Extended Kalman Filter (EKF). This algorithm is based in the data fusion of the classical sensors; an Inertial Measurement Unit (IMU), an ultrasonic sensor and a vision system. The algorithms are validated onboard in flight tests to realize autonomous navigation of the quadrotor vehicle. The most important results are depicted in some graphs.","PeriodicalId":322089,"journal":{"name":"2013 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Observer-control scheme for autonomous navigation: Flight tests validation in a quadrotor vehicle\",\"authors\":\"L. E. Munoz, P. Castillo, P. Garcia\",\"doi\":\"10.1109/ICUAS.2013.6564762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present in this paper an improvement of a nonlinear control algorithm based on the Lyapunov analysis and the saturation functions, to realize autonomous navigation of a quadrotor vehicle. The algorithm is analyzed and the convergence of the states is ameliorated, in addition, the stability analysis in closed-loop system is proved with these new conditions. In order to locate the aerial vehicle a new position estimation algorithm is developed using the dead-reckoning technique with the Extended Kalman Filter (EKF). This algorithm is based in the data fusion of the classical sensors; an Inertial Measurement Unit (IMU), an ultrasonic sensor and a vision system. The algorithms are validated onboard in flight tests to realize autonomous navigation of the quadrotor vehicle. The most important results are depicted in some graphs.\",\"PeriodicalId\":322089,\"journal\":{\"name\":\"2013 International Conference on Unmanned Aircraft Systems (ICUAS)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Unmanned Aircraft Systems (ICUAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICUAS.2013.6564762\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS.2013.6564762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Observer-control scheme for autonomous navigation: Flight tests validation in a quadrotor vehicle
We present in this paper an improvement of a nonlinear control algorithm based on the Lyapunov analysis and the saturation functions, to realize autonomous navigation of a quadrotor vehicle. The algorithm is analyzed and the convergence of the states is ameliorated, in addition, the stability analysis in closed-loop system is proved with these new conditions. In order to locate the aerial vehicle a new position estimation algorithm is developed using the dead-reckoning technique with the Extended Kalman Filter (EKF). This algorithm is based in the data fusion of the classical sensors; an Inertial Measurement Unit (IMU), an ultrasonic sensor and a vision system. The algorithms are validated onboard in flight tests to realize autonomous navigation of the quadrotor vehicle. The most important results are depicted in some graphs.