On the Regret of H∞ Control
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Abstract (arXiv)
The H∞ synthesis approach is a cornerstone robust control design technique, but is known to be conservative in some cases. The objective of this paper is to quantify the additional cost the controller incurs planning for the worst-case scenario, by adopting an approach inspired by regret from online learning. We define the textitdisturbance-reality gap as the difference between the predicted worst-case disturbance signal and the actual realization. The regret is shown to scale with the norm of this textitgap, which turns out to have a similar structure to that of the certainty equivalent controller with inaccurate predictions, obtained here in terms of the textitprediction error norm.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Mar 2022.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1.
5 papers.
- 2022Implications of Regret on Stability of Linear Dynamical Systemscited by 3
- 2023Adaptive Online Non-stochastic Controlcited by 3
- 2024Optimistic Online Non-stochastic Control via FTRLcited by 3
- 2022Optimal Competitive-Ratio Controlcited by 2
- 2025Online Convex Optimization and Integral Quadratic Constraints: An automated approach to regret analysiscited by 1
- 2025Online Convex Optimization and Integral Quadratic Constraints: An automated approach to regret analysis30 Mar 2025
- 2024Optimistic Online Non-stochastic Control via FTRL4 Apr 2024
- 2023Adaptive Online Non-stochastic Control2 Oct 2023
- 2022Implications of Regret on Stability of Linear Dynamical Systems14 Nov 2022
- 2022Optimal Competitive-Ratio Control3 Jun 2022