Robust LPV Fault Diagnosis Using the Set-Based Approach for Autonomous Ground Vehicles

This paper proposes a robust fault diagnosis method for Autonomous Ground Vehicles (AGVs) modeled as a Linear Parameter Varying (LPV) system with bounded uncertainties. The proposed approach combines the zonotope-based Set-Membership Approach (SMA) and Set Invariance Approach (SIA). Firstly, an online fault detection strategy based on zonotopic set-membership state estimation is introduced, where the optimal observer gain is calculated offline by solving LMI optimization problems. To characterize the Minimum Detectable Fault (MDF) and Minimum Isolable Fault (MIF), the invariant residual sets are first obtained for the system operated in healthy and faulty modes. The proposed method relies on the propagation of the zonotopic state estimation error in steady state based on SIA. Then, MDF and MIF are characterized for several types of faults by solving optimization problems subject to set separation conditions. Finally, experiment validations using a prototype vehicle are performed to illustrate the effectiveness of the proposed approach.

• Record URL:
  • http://dx.doi.org/10.1109/TITS.2024.3394518
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Copyright © 2024, IEEE.
• Authors:
  • Zhang, Shuang
  • 0000-0003-4528-3326
  • Puig, Vicenç
  • 0000-0002-6364-6429
  • Ifqir, Sara
  • 0000-0002-6707-5811
• Publication Date: 2024-8

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 9078-9090
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 25
  • Issue Number: 8
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Flaw detection; Mathematical models; Prototype tests; Uncertainty
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Vehicles and Equipment;

Filing Info

• Accession Number: 01936683
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 12 2024 9:43AM