Mixed Fuzzy Sliding-Mode Tracking with Backstepping Formation Control for Multi-Nonholonomic Mobile Robots Subject to Uncertainties: Category (3),(5)

Hsiu Ming Wu, Mansour Karkoub, Chih Lyang Hwang

Research output: Contribution to journalArticle

10 Citations (Scopus)


This paper aims at attaining one-leader & two-followers (1L-2F) formation control of multi-nonholonomic mobile robot (multi-NMR) systems subject to uncertainties and, at the same time, achieves trajectory-tracking of the leader NMR. To begin, the tracking error between the leader and a virtual reference robot is defined. Then, the extension to a leader-follower formation control structure is utilized to define the formation error (i.e., separation and orientation errors) between the leader and the followers. It has been proven that fuzzy sliding-mode tracking control (FSMTC) and backstepping formation control (BFC) can improve performance and stability when the overall closed-loop system is subject to uncertainties. Therefore, FSMTC and BFC are used for trajectory tracking of the leader NMR and formation control for two followers with respect to the leader, respectively. The stability of the closed-loop multi-NMR systems, i.e., trajectory tracking and formation control, is demonstrated through Lyapunov stability criteria. Finally, to validate the theoretical developments, computer simulations are conducted which prove the effectiveness, efficiency and robustness of the proposed scheme.

Original languageEnglish
Pages (from-to)73-86
Number of pages14
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number1
Publication statusPublished - 8 Jul 2015



  • Backstepping formation control
  • Fuzzy slidingf-mode tracking control
  • Leader-follower formation control
  • Lyapunov stability criteria
  • Multi-nonholonomic mobile robots
  • Virtual reference robot

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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