Resilient time-varying formation tracking for mobile robot networks under deception attacks on positioning

Yen Chen Liu, Kai Yuan Liu, Zhuoyuan Song

Research output: Contribution to journalArticlepeer-review


This paper investigates the resilient control, analysis, recovery, and operation of mobile robot networks in time-varying formation tracking under deception attacks on global positioning. Local and global tracking control algorithms are presented to ensure redundancy of the mobile robot network and to retain the desired functionality for better resilience. Lyapunov stability analysis is utilized to show the boundedness of the formation tracking error and the stability of the network under various attack modes. A performance index is designed to compare the efficiency of the proposed formation tracking algorithms in situations with or without positioning attacks. Subsequently, a communication-free decentralized cooperative localization approach based on extended information filters is presented for positioning estimate recovery where the identification of positioning attacks is based on Kullback–Leibler divergence. A gain-tuning resilient operation is proposed to strategically synthesize formation control and cooperative localization for accurate and rapid system recovery from positioning attacks. The proposed methods are tested using both numerical simulation and experimental validation with a team of quadrotors.

Original languageEnglish
Pages (from-to)6308-6328
Number of pages21
JournalInternational Journal of Robust and Nonlinear Control
Issue number11
Publication statusPublished - 2023 Jul 25

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Chemical Engineering(all)
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Resilient time-varying formation tracking for mobile robot networks under deception attacks on positioning'. Together they form a unique fingerprint.

Cite this