Robust Leader-Follower Formation Tracking Control of Multiple Underactuated Surface Vessels  

作　　者：彭周华 王丹 兰维瑶 孙刚 

机构地区：[1]Marine Engineering College,Dalian Maritime University [2]Department of Automation,Xiamen University

出　　处：《China Ocean Engineering》2012年第3期521-534,共14页中国海洋工程（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos. 60674037,61074017 and 61074004);the Program for New Century Excellent Talents in Universities (Grant No. NCET-09-0674);the Program for Liaoning Excellent Talents in Universities (Grant No. 2009R06)

摘　　要：This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation. The formation is achieved by the follower to track a virtual target defined relative to the leader. A robust adaptive target tracking law is proposed by using neural network and backstepping techniques. The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces, nonlinear damping, unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning. Based on Lyapunov analysis, the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin. Simulation results demonstrate the effectiveness of the control strategy.This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation. The formation is achieved by the follower to track a virtual target defined relative to the leader. A robust adaptive target tracking law is proposed by using neural network and backstepping techniques. The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces, nonlinear damping, unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning. Based on Lyapunov analysis, the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin. Simulation results demonstrate the effectiveness of the control strategy.

关 键 词：marine surface vessel formation control neural network BACKSTEPPING LEADER-FOLLOWER 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] U664.82[自动化与计算机技术—控制科学与工程]