Liang Xiao, Qu Xingru, Wang Ning, Li Ye
School of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, 116026, PR China.
School of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, 116026, PR China.
ISA Trans. 2021 Jun;112:271-280. doi: 10.1016/j.isatra.2020.11.025. Epub 2020 Nov 28.
This article mainly researches the problem of distributed finite-time coordinated path-following for under-actuated autonomous surface vehicles (ASVs) within a network swarm. Each vehicle in swarm system suffers from velocity restrictions and multiple uncertainties including parameter perturbations and time-varying environment disturbances. Based on the constructed bionic swarm pattern and potential function, the swarm velocity guidance (SVG) with self-organization and collision avoidance is developed to guide ASV surge velocities and heading angles simultaneously. A distributed observer by adding correction terms to the vehicle model is involved to identify the lumped uncertainties, and the estimations are utilized as feed-forward compensation to weaken the uncertainty impact, thus achieving high tracking precision. By using asymmetric barrier Lyapunov function, the uncertainty observer based distributed surge and heading kinetics controllers under physical restrictions are devised to guarantee that the guided signals generated by SVG are tracked within finite time. Through simulation studies of swarm path-following, it is demonstrated that the designed control approach is feasible and efficient for multiple uncertain under-actuated ASVs.
本文主要研究网络群体中欠驱动自主水面航行器（ASV）的分布式有限时间协同路径跟踪问题。群体系统中的每艘航行器都受到速度限制以及包括参数摄动和时变环境干扰在内的多种不确定性影响。基于所构建的仿生群体模式和势函数，开发了具有自组织和避碰功能的群体速度引导（SVG）方法，以同时引导ASV的纵荡速度和航向角。通过在航行器模型中添加校正项设计了一种分布式观测器来识别集中不确定性，并将估计值用作前馈补偿以减弱不确定性影响，从而实现高跟踪精度。利用非对称障碍李雅普诺夫函数，设计了物理限制下基于不确定性观测器的分布式纵荡和航向动力学控制器，以确保在有限时间内跟踪由SVG生成的引导信号。通过群体路径跟踪的仿真研究，证明了所设计的控制方法对于多个不确定欠驱动ASV是可行且有效的。
