Robust H2/H-infinity control under stochastic requirements: minimizing conditional value-at-risk instead of worst-case performance
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911575478108160 |
|---|---|
| author | Kassarian, Ervan Sanfedino, Francesco Alazard, Daniel Marrazza, Andrea |
| author_facet | Kassarian, Ervan Sanfedino, Francesco Alazard, Daniel Marrazza, Andrea |
| contents | Conventional robust H2/H-infinity control minimizes the worst-case performance, often leading to a conservative design driven by very rare parametric configurations. To reduce this conservatism while taking advantage of the stochastic properties of Monte Carlo sampling and its compatibility with parallel computing, we introduce an alternative paradigm that optimizes the controller with respect to a stochastic criterion, namely the conditional value at risk. We present the problem formulation and discuss several open challenges toward a general synthesis framework. The potential of this approach is illustrated on a mechanical system, where it significantly improves overall performance by tolerating some degradation in very rare worst-case scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_18356 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust H2/H-infinity control under stochastic requirements: minimizing conditional value-at-risk instead of worst-case performance Kassarian, Ervan Sanfedino, Francesco Alazard, Daniel Marrazza, Andrea Systems and Control Optimization and Control Conventional robust H2/H-infinity control minimizes the worst-case performance, often leading to a conservative design driven by very rare parametric configurations. To reduce this conservatism while taking advantage of the stochastic properties of Monte Carlo sampling and its compatibility with parallel computing, we introduce an alternative paradigm that optimizes the controller with respect to a stochastic criterion, namely the conditional value at risk. We present the problem formulation and discuss several open challenges toward a general synthesis framework. The potential of this approach is illustrated on a mechanical system, where it significantly improves overall performance by tolerating some degradation in very rare worst-case scenarios. |
| title | Robust H2/H-infinity control under stochastic requirements: minimizing conditional value-at-risk instead of worst-case performance |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2512.18356 |