{"title":"A Novel Leader-Follower Framework for Control of Helicopter Formation","authors":"M. Saffarian, F. Fahimi","doi":"10.1109/AERO.2007.352757","DOIUrl":null,"url":null,"abstract":"A framework for formation control of a group of autonomous helicopters is presented. We introduced two control schemes named as I - alpha and I - I, which are tailored to control the relative positions of a helicopter constrained by either one or two neighboring leaders, respectively. To stabilize the internal formation parameters of these schemes, a nonlinear model predictive controller is developed. The controller finds the future control commands by optimizing a cost function, which includes formation parameter errors among other parameters such as control forces. The gradient descent method is considered as a suitable optimizer candidate for our approach. The design steps of the I - I controller is presented in this work. By designing both the two l - alpha and I - I control schemes, any user-defined three dimensional grid pattern could be achieved by a group of autonomous helicopters.","PeriodicalId":6295,"journal":{"name":"2007 IEEE Aerospace Conference","volume":"11 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Aerospace Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AERO.2007.352757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
A framework for formation control of a group of autonomous helicopters is presented. We introduced two control schemes named as I - alpha and I - I, which are tailored to control the relative positions of a helicopter constrained by either one or two neighboring leaders, respectively. To stabilize the internal formation parameters of these schemes, a nonlinear model predictive controller is developed. The controller finds the future control commands by optimizing a cost function, which includes formation parameter errors among other parameters such as control forces. The gradient descent method is considered as a suitable optimizer candidate for our approach. The design steps of the I - I controller is presented in this work. By designing both the two l - alpha and I - I control schemes, any user-defined three dimensional grid pattern could be achieved by a group of autonomous helicopters.