Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2506.19829 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866914342717358080 |
|---|---|
| author | Fotiadis, Filippos Topcu, Ufuk |
| author_facet | Fotiadis, Filippos Topcu, Ufuk |
| contents | We develop a feedback controller that minimizes the observability of a set of adversarial sensors of a linear system, while adhering to strict closed-loop performance constraints. We quantify the effectiveness of adversarial sensors using the trace of their observability Gramian and its inverse, capturing both average observability and the least observable state directions of the system. We derive theoretical lower bounds on these metrics under performance constraints, characterizing the fundamental limits of observability reduction as a function of the performance trade-off. Finally, we show that the performance-constrained optimization of the Gramian's trace can be formulated as a one-shot semidefinite program, while we address the optimization of its inverse through sequential semidefinite programming. Simulations on an aircraft show how the proposed scheme yields controllers that deteriorate adversarial observability while having near-optimal performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_19829 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Adversarial Observability and Performance Trade-offs in Optimal Control Fotiadis, Filippos Topcu, Ufuk Systems and Control Optimization and Control We develop a feedback controller that minimizes the observability of a set of adversarial sensors of a linear system, while adhering to strict closed-loop performance constraints. We quantify the effectiveness of adversarial sensors using the trace of their observability Gramian and its inverse, capturing both average observability and the least observable state directions of the system. We derive theoretical lower bounds on these metrics under performance constraints, characterizing the fundamental limits of observability reduction as a function of the performance trade-off. Finally, we show that the performance-constrained optimization of the Gramian's trace can be formulated as a one-shot semidefinite program, while we address the optimization of its inverse through sequential semidefinite programming. Simulations on an aircraft show how the proposed scheme yields controllers that deteriorate adversarial observability while having near-optimal performance. |
| title | Adversarial Observability and Performance Trade-offs in Optimal Control |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2506.19829 |