{"title":"Coordinated UAV Standoff Tracking of Moving Target Based on Lyapunov Vector Fields","authors":"Tagir Z. Muslimov","doi":"10.1109/NIR50484.2020.9290189","DOIUrl":"https://doi.org/10.1109/NIR50484.2020.9290189","url":null,"abstract":"This paper proposes an approach to cooperative tracking of a moving target using a system of multiple fixed-wing unmanned aerial vehicles (UAVs). In this scenario, the task is to coordinate a UAV group so that it could follow a moving circular path while keeping specified (and not necessarily identical) spacing. Many papers dwell upon path following problems for UAV formations; solutions they propose include Lyapunov vector fields. This article particularly uses a different method that revolves around a decentralized guidance Lyapunov vector field for path following; this field is non-uniform in both direction and magnitude. The advantage of proposed strategy lies in the global asymptotic stability it provides, which helps not only create a UAV formation around the target faster, but also keep it stable shall the formation fail to precisely follow its specified orbit. We analyzed the consensus-based coordination architecture in the form of a decentralized open chain. For space considerations, this paper only describes a target moving at a constant speed. MATLAB/Simulink modeling based on complete non-linear flying-wing UAV models shows that the proposed approach efficient.","PeriodicalId":274976,"journal":{"name":"2020 International Conference Nonlinearity, Information and Robotics (NIR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129382039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cognitive interaction via a brain-to-brain interface","authors":"V. Maksimenko, V. Grubov","doi":"10.1109/NIR50484.2020.9290200","DOIUrl":"https://doi.org/10.1109/NIR50484.2020.9290200","url":null,"abstract":"We developed noninvasive brain-to-brain interface for dynamical redistribution of cognitive load between subjects according to their current performances during shared cognitive task. As a result, a participant who exhibits higher cognitive performance is subjected to a higher workload, while his/her partner receives a lower workload. We demonstrate that dynamical workload redistribution allows to increase overall cognitive performance in the pair of interacting subjects.","PeriodicalId":274976,"journal":{"name":"2020 International Conference Nonlinearity, Information and Robotics (NIR)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124228706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ANN and elements of differentional games in the model of regulated wheel slippage process in a braking mode","authors":"A. Fedin, Y. Kalinin, E. Marchuk","doi":"10.1109/NIR50484.2020.9290165","DOIUrl":"https://doi.org/10.1109/NIR50484.2020.9290165","url":null,"abstract":"Processes of braking system operations of the ground wheeled vehicle are complex nonlinear dynamic processes. When a problem of modeling vehicle braking process is setting it is considered rational to set the one in a form of the antagonistic differential game and to represent one of the antagonists - the road surface - in a form of unknown disturbance. It is considered rational to choose an artificial neural network (ANN) as a control element and flexible approximator that has properties of self-learning.","PeriodicalId":274976,"journal":{"name":"2020 International Conference Nonlinearity, Information and Robotics (NIR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133637494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}