A System Level Approach to Regret Optimal Control
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Abstract (arXiv)
We present an optimisation-based method for synthesising a dynamic regret optimal controller for linear systems with potentially adversarial disturbances and known or adversarial initial conditions. The dynamic regret is defined as the difference between the true incurred cost of the system and the cost which could have optimally been achieved under any input sequence having full knowledge of all future disturbances for a given disturbance energy. This problem formulation can be seen as an alternative to classical H2- or H_∞-control. The proposed controller synthesis is based on the system level parametrisation, which allows reformulating the dynamic regret problem as a semi-definite problem. This yields a new framework that allows to consider structured dynamic regret problems, which have not yet been considered in the literature. For known pointwise ellipsoidal bounds on the disturbance, we show that the dynamic regret bound can be improved compared to using only a bounded energy assumption and that the optimal dynamic regret bound differs by at most a factor of frac2π from the computed solution. Furthermore, the proposed framework allows guaranteeing state and input constraint satisfaction.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Feb 2022.
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Citing papers per year: 2022: 3; 2023: 1.
4 papers.
- 2022Implications of Regret on Stability of Linear Dynamical Systemscited by 3
- 2023A Distributionally Robust Approach to Regret Optimal Control using the Wasserstein Distancecited by 3
- 2022Optimal Competitive-Ratio Controlcited by 2
- 2022Follow the Clairvoyant: an Imitation Learning Approach to Optimal Controlcited by 0
- 2023A Distributionally Robust Approach to Regret Optimal Control using the Wasserstein Distance13 Apr 2023
- 2022Implications of Regret on Stability of Linear Dynamical Systems14 Nov 2022
- 2022Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control14 Nov 2022
- 2022Optimal Competitive-Ratio Control3 Jun 2022