In this paper,we consider a multi-UAV surveillance scenario where a team of unmanned aerial vehicles(UAVs)synchronously covers an area for monitoring the ground conditions.In this scenario,we adopt the leader-follower...In this paper,we consider a multi-UAV surveillance scenario where a team of unmanned aerial vehicles(UAVs)synchronously covers an area for monitoring the ground conditions.In this scenario,we adopt the leader-follower control mode and propose a modified Lyapunov guidance vector field(LGVF)approach for improving the precision of surveillance trajectory tracking.Then,in order to adopt to poor communication conditions,we propose a prediction-based synchronization method for keeping the formation consistently.Moreover,in order to adapt the multi-UAV system to dynamic and uncertain environment,this paper proposes a hierarchical dynamic task scheduling architecture.In this architecture,we firstly classify all the algorithms that perform tasks according to their functions,and then modularize the algorithms based on plugin technology.Afterwards,integrating the behavior model and plugin technique,this paper designs a three-layer control flow,which can efficiently achieve dynamic task scheduling.In order to verify the effectiveness of our architecture,we consider a multi-UAV traffic monitoring scenario and design several cases to demonstrate the online adjustment from three levels,respectively.展开更多
A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decompose...A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decomposed algorithm based on Benders' decomposition.The model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,respectively.Test results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 min.The test results also illustrate that the proposed approach is efficient and suitable for large system calculation.展开更多
基金Project(2017YFB1301104)supported by the National Key Research and Development Program of ChinaProjects(61906212,61802426)supported by the National Natural Science Foundation of China。
文摘In this paper,we consider a multi-UAV surveillance scenario where a team of unmanned aerial vehicles(UAVs)synchronously covers an area for monitoring the ground conditions.In this scenario,we adopt the leader-follower control mode and propose a modified Lyapunov guidance vector field(LGVF)approach for improving the precision of surveillance trajectory tracking.Then,in order to adopt to poor communication conditions,we propose a prediction-based synchronization method for keeping the formation consistently.Moreover,in order to adapt the multi-UAV system to dynamic and uncertain environment,this paper proposes a hierarchical dynamic task scheduling architecture.In this architecture,we firstly classify all the algorithms that perform tasks according to their functions,and then modularize the algorithms based on plugin technology.Afterwards,integrating the behavior model and plugin technique,this paper designs a three-layer control flow,which can efficiently achieve dynamic task scheduling.In order to verify the effectiveness of our architecture,we consider a multi-UAV traffic monitoring scenario and design several cases to demonstrate the online adjustment from three levels,respectively.
基金Projects(51007047,51077087)supported by the National Natural Science Foundation of ChinaProject(2013CB228205)supported by the National Key Basic Research Program of China+1 种基金Project(20100131120039)supported by Higher Learning Doctor Discipline End Scientific Research Fund of the Ministry of Education Institution,ChinaProject(ZR2010EQ035)supported by the Natural Science Foundation of Shandong Province,China
文摘A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decomposed algorithm based on Benders' decomposition.The model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,respectively.Test results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 min.The test results also illustrate that the proposed approach is efficient and suitable for large system calculation.
