Distributed extended state observer based formation tracking control of under-actuated unmanned surface vehicles with input and state quantization

被引:1
作者
Ma, Yifan [1 ]
Ning, Jun [1 ]
Li, Tieshan [2 ]
Liu, Lu [3 ]
机构
[1] Dalian Maritime Univ, Coll Nav, Dalian 116026, Peoples R China
[2] Univ Elect Sci & Technol China, Coll Automat Engn, Chengdu 611731, Peoples R China
[3] Dalian Maritime Univ, Coll Marine Elect Engn, Dalian 116026, Peoples R China
关键词
Unmanned surface vehicles; Formation tracking control; Distributed extended state observer; Input and state quantization; Adaptive quantized feedback control;
D O I
10.1016/j.oceaneng.2024.118872
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This paper delves into the distributed formation control of unmanned surface vehicles (USVs) under conditions of simultaneous input and state quantization. The primary objective is to ensure that USVs in the formation can effectively follow the specified trajectory in a bandwidth-limited communication environment. A distributed extended state observer (ESO) is proposed to observe the state information of the virtual leader in the USV formation. Furthermore, another ESO is introduced to address the impact of uncertainty terms in the ship model and quantized state variables during communication on the formation control system. Subsequently, the USVs formation guidance laws are formulated in the kinematics subsystem. In addition, the quantized control laws are described linearly in the kinetics subsystem so that the USVs distributed formation controller does not need to anticipate specific information about the quantization parameters. Meanwhile, the USVs formation tracking underlying control laws are designed in the quantized environment to achieve the tracking of the desired kinematic guidance signal. Then, the stability of the designed distributed formation tracking control system for USVs is proved using Lyapunov stability theory. Finally, the effectiveness of the proposed strategy is validated through two sets of simulation experiments, providing empirical evidence of its practical applicability.
引用
收藏
页数:13
相关论文
共 49 条
  • [41] Barrier Lyapunov Function-based adaptive prescribed-time extended state observers design for unmanned surface vehicles subject to unknown disturbances
    Zhao, Jie
    Cai, Chengtao
    Liu, Yongchao
    OCEAN ENGINEERING, 2023, 270
  • [42] Distributed extended state observer design and dual-side dynamic event-triggered output feedback anti-disturbance control for nonlinear interconnected systems with quantization
    Sun, Haibin
    Liu, Yujie
    Jiao, Ticao
    Hou, Linlin
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2024, 361 (09):
  • [43] Reinforcement learning-based trajectory tracking optimal control of unmanned surface vehicles in narrow water areas
    Wei, Ziping
    Du, Jialu
    ISA TRANSACTIONS, 2025, 159 : 152 - 164
  • [44] Periodic event-triggered adaptive neural output feedback tracking control of unmanned surface vehicles under replay attacks
    Zhu, Guibing
    Xu, Zhengyue
    Gao, Yun
    Yu, Yalei
    Li, Lei
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2025, 146
  • [45] Fully distributed dynamic event-triggered formation-containment control for networked unmanned surface vehicles with intermittent wireless network communications
    Zhang, Zhen
    Huang, Bing
    Zhou, Xiaotao
    Peng, Hua
    ISA TRANSACTIONS, 2025, 156 : 202 - 216
  • [46] Distributed extended state observer design and output feedback anti-disturbance control for nonlinear interconnected systems: A dynamic memory event-triggered mechanism
    Liu, Yujie
    Sun, Haibin
    Hou, Linlin
    ASIAN JOURNAL OF CONTROL, 2024, 26 (01) : 227 - 245
  • [47] Fixed-time fuzzy formation control for underactuated surface vehicles based on a novel trajectory-guiding strategy under model uncertainties
    Wang, Zheng
    Zhao, Yongsheng
    Mu, Dongdong
    Sun, Xiaojie
    Wang, Yiqi
    OCEAN ENGINEERING, 2025, 327
  • [48] Safe-critical formation reconfiguration of multiple unmanned surface vehicles subject to static and dynamic obstacles based on guiding vector fields and fixed-time control barrier functions
    Gong, Xiaoxuan
    Liu, Lu
    Peng, Zhouhua
    OCEAN ENGINEERING, 2022, 250
  • [49] Terminal sliding-mode disturbance observer-based finite-time adaptive-neural formation control of autonomous surface vessels under output constraints
    Naderolasli, Amir
    Shojaei, Khoshnam
    Chatraei, Abbas
    ROBOTICA, 2023, 41 (01) : 236 - 258