Fast Fixed-Time Output Multi-Formation Tracking of Networked Autonomous Surface Vehicles: A Mathematical Induction Method

In this paper, the authors aim to exploit an effective way to solve the output multi-formation tracking problem of the networked autonomous surface vehicles (ASVs) in a fast fixed time manner. Specifically, addressing the output multi-formation tracking problem implies that 1) the networked ASVs are divided into multiple interconnected subnetworks with respect to multiple targets; 2) for each subnetwork, the outputs of the networked ASVs form a desired geometric formation with exchanging the local interactions. Besides, solving the fast fixed-time tracking problem in this paper implies that 1) the convergence time is independent of the initial conditions; 2) the system states are forced to reach the employed nonsingular fixed-time sliding surface in a prescribed time, which thus called fast fixed-time control. Then, based on a time-related function and a nonsingular fixed-time sliding surface, a hierarchical fast fixed-time control algorithm is proposed to solve the aforementioned problem within a fast fixed time being independent of the initial conditions. Furthermore, by employing the Lyapunov argument and mathematical induction, the authors present the sufficient conditions for fast fixed-time convergence of the tracking errors with respect to multiple targets. Finally, numerous simulation examples are presented to demonstrate the effectiveness of the proposed control algorithm.

• Record URL:
  • http://dx.doi.org/10.1109/TVT.2022.3233887
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
• Supplemental Notes:
  • Copyright © 2023, IEEE.
• Authors:
  • Ding, Teng-Fei
  • Xu, Kun-Ting
  • Ge, Ming-Feng
  • 0000-0002-6828-0147
  • Park, Ju H
  • Liang, Chang-Duo
• Publication Date: 2023-5

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 5769-5781
• Serial:
  • IEEE Transactions on Vehicular Technology
  • Volume: 72
  • Issue Number: 5
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 0018-9545
  • Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25

Subject/Index Terms

• TRT Terms: Algorithms; Autonomous vehicles; Control systems; Mathematical methods; Ships; Tracking systems
• Subject Areas: Marine Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01882959
• Record Type: Publication
• Files: TRIS
• Created Date: May 23 2023 10:09AM