Neural Adaptive Flocking Control of Networked Underactuated Autonomous Surface Vehicles in the Presence of Uncertain Dynamics
This paper considers the leader-follower flocking problem of networked underactuated autonomous surface vehicles (ASVs) in the presence of uncertain dynamics. By employing the graph theory and neural networks, a distributed adaptive flocking controller is developed for the vehicles to achieve the motion synchronization with the leader. A collective potential function is used to avoid collisions between the vehicles. Based on Lyapunov stability analysis, the developed neural flocking algorithm guarantees that all the ASVs’ headings and speeds are synchronous with the leader for any undirected connected communication network. Simulation results using an experimental ship model are given to show the efficacy of the proposed strategy.
Flocking Control Neural Networks Autonomous Surface Vehicles Uncertain Dynamics
Zhouhua Peng Dan Wang Weiyao Lan Gang Sun Langtao Yan
Marine Engineering College, Dalian Maritime University, Dalian 116026, P. R. China Department of Automation, Xiamen University, Xiamen 361005, P. R. China
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
2865-2870
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）