2403.13471
Data-Driven Reduced-Order Unknown-Input Observers
Giorgia Disarò, Maria Elena Valcher
correctmedium confidence
- Category
- Not specified
- Journal tier
- Strong Field
- Processed
- Sep 28, 2025, 12:56 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The paper’s Theorem 9 characterizes data-driven rUIO existence via the linear relation Xf,1 = [S1 S2 S3 S4][Up; Yp; Yf; Xp,1] with S4 Schur and provides the parameterization AUIO=S4, Bu_UIO=S1, By_UIO=S2+S4S3, DUIO=S3; this is precisely what the candidate solution proves, matching Proposition 6 and Theorem 9. The candidate’s necessity and construction align exactly with the paper’s mapping. The only gap is a proof step that invokes a full-row-rank assumption on a stacked matrix including the unmeasured disturbance; the paper instead correctly bases sufficiency on the kernel-inclusion/compatibility condition, avoiding dependence on unknown d. With that minor fix, the candidate’s proof lines up with the paper’s results and intent (Definition 1, Proposition 6, Theorem 9).
Referee report (LaTeX)
\textbf{Recommendation:} minor revisions \textbf{Journal Tier:} strong field \textbf{Justification:} The core equivalence and parameterization for data-driven rUIOs are established cleanly and shown to match the model-based conditions. The acceptor-based framework and kernel-inclusion condition are appropriate and avoid reliance on unmeasured disturbances. Clarity is good overall, but a few assumptions could be signposted earlier to make the paper fully self-contained for readers who are new to this line of work.