Chattering-Free Fault-Tolerant Cluster Control and Fault Direction Identification for HIL UAV Swarm with Pre-Specified Performance

Pei Ming Liu, Xiang Gui Guo, Jian Liang Wang, Daniel Coutinho, Lihua Xie

Research output: Journal PublicationArticlepeer-review

Abstract

In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop (HIL) swarm unmanned aerial vehicles (UAVs) in the presence of possible non-identical and unknown direction faults (NUDFs) in the yaw chan-nel. The control strategy begins with the design of a pre-specified performance event-triggered observer for each individual UAV. These observers estimate the outputs of the human controlled UAVs, and simultaneously achieve the distributed design of actual control signals as well as cluster consensus of the observer output. It is worth mentioning that these observers require neither the high-order derivatives of the human controlled UAVs' output nor a priori knowledge of the initial conditions. The fault-tolerant controller realizes the pre-specified performance output regulation through error transformation and the Nussbaum function. It should be pointed out that there are no chattering caused by the jump of the Nussbaum function when a reverse fault occurs. In addition, to provide a basis for further solving the problem of physical malfunctions, a fault direction identification algorithm is proposed to accurately identify whether a reverse fault has occurred. Simulation results verify the effectiveness of the proposed control and fault direction identification strategies when the reverse faults occur.

Original languageEnglish
Pages (from-to)183-197
Number of pages15
JournalIEEE/CAA Journal of Automatica Sinica
Volume12
Issue number1
DOIs
Publication statusPublished - 2025
Externally publishedYes

Keywords

  • Chattering-free
  • cluster consensus
  • fault direction identification
  • human-in-the-loop (HIL)
  • nonidentical and unknown direction faults (NUDFs)
  • pre-specified performance
  • swarm unmanned aerial vehicles (UAVs)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Control and Optimization
  • Artificial Intelligence

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