中国舰船研究2025，Vol.20Issue(1)：309-316,8.DOI:10.19693/j.issn.1673-3185.03609
海洋自主水面船舶跨水域自适应神经控制
Adaptive neural control for marine autonomous surface ships in cross-water scenarios
摘要
Abstract
[Objective]An adaptive neural control(ANC)scheme with specified performance is proposed for the tracking control of marine autonomous surface ships(MASS)subject to uncertain model parameters and unknown external environmental disturbances in cross-water scenarios.[Methods]Under the back-stepping design framework,a neural network is utilized to approximate the uncertain model parameters and unknown external environmental disturbances.A novel specified performance function is constructed and combined with the barrier Lyapunov function(BLF)to transform the cross-water design,while the dynamic surface control technique is employed to reduce the system's computational complexity.Stability analysis is then performed by means of Lyapunov theory to demonstrate that all signals within the control system are bounded.[Results]The simulation results show that the designed control scheme is not only capable of solv-ing the cross-water tracking control of MASS,but that the tracking error can satisfy the convergence to a giv-en bounded range within a predefined time offline.[Conclusion]The results of this study can solve the cross-water tracking control problems of MASS and provide valuable references for the tracking control of ships in restricted waters,giving them practical engineering significance.关键词
无人船/海洋自主水面船舶/神经网络/自适应神经控制/障碍李雅普诺夫函数/跨水域场景Key words
unmanned vehicles/marine autonomous surface ship(MASS)/neural networks/adaptive neur-al control(ANC)/barrier Lyapunov function(BLF)/cross-water scenarios分类
交通运输引用本文复制引用
叶翔,陈超,贾建雄,陈航..海洋自主水面船舶跨水域自适应神经控制[J].中国舰船研究,2025,20(1):309-316,8.基金项目
浙江省"尖兵""领雁"研发攻关计划资助项目(2023C03181) （2023C03181）
浙江海洋大学企业行业难题攻关资助项目(1118106412301,1118106412204) （1118106412301,1118106412204）
