典型文献
A Scalable Adaptive Approach to Multi-Vehicle Formation Control with Obstacle Avoidance
文献摘要:
This paper deals with the problem of distributed formation tracking control and obstacle avoidance of multi-vehicle systems(MVSs)in complex obstacle-laden environments.The MVS under consideration consists of a leader vehicle with an unknown control input and a group of follower vehicles,connected via a directed interaction topology,subject to simultaneous unknown heterogeneous nonlinearities and external disturbances.The central aim is to achieve effective and collision-free formation tracking control for the nonlinear and uncertain MVS with obstacles encountered in formation maneuvering,while not demanding global information of the interaction topology.Toward this goal,a radial basis function neural network is used to model the unknown nonlinearity of vehicle dynamics in each vehicle and repulsive potentials are employed for obstacle avoidance.Furthermore,a scalable distributed adaptive formation tracking control protocol with a built-in obstacle avoidance mechanism is developed.It is proved that,with the proposed protocol,the resulting formation tracking errors are uniformly ultimately bounded and obstacle collision avoidance is guaranteed.Comprehensive simulation results are elaborated to substantiate the effectiveness and the promising collision avoidance performance of the proposed scalable adaptive formation control approach.
文献关键词:
中图分类号:
作者姓名:
Xiaohua Ge;Qing-Long Han;Jun Wang;Xian-Ming Zhang
作者机构:
School of Science,Computing and Engineering Technologies,Swinburne University of Technology,Melbourne,VIC 3122,Australia;Department of Computer Science and School of Data Science,City University of Hong Kong,China
文献出处:
引用格式:
[1]Xiaohua Ge;Qing-Long Han;Jun Wang;Xian-Ming Zhang-.A Scalable Adaptive Approach to Multi-Vehicle Formation Control with Obstacle Avoidance)[J].自动化学报(英文版),2022(06):990-1004
A类:
MVSs
B类:
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AB值:
0.591104
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