Data-Driven Approach to the Design of Fault Isolation Filter

This paper proposes a data-driven approach to design a fault isolation filter to isolate actuator faults in discrete linear time-invariant systems. It is shown that a fault isolation filter can be obtained directly from the system input and output data without any knowledge about the system model. The subspace identification technique is applied to obtain the fault detectability indices and the fault detectability matrix directly from the data. The design procedure involves a singular value decomposition and an LU factorization with partial pivoting. The identified fault isolation filter is able to isolate multiple faults with only a single filter, which significantly reduces the online computational efforts needed for fault isolation. A simulation example is given to illustrate the proposed data-driven approach.

• Publication year

  2025

• Venue

  American Control Conference

• Publication date

  2025-07-08

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.23919/ACC63710.2025.11108028
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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