Performance bounds for the mean-field limit of constrained dynamics
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Abstract (arXiv)
In this work we are interested in the mean-field formulation of kinetic models under control actions where the control is formulated through a model predictive control strategy (MPC) with varying horizon. The relation between the (usually hard to compute) optimal control and the MPC approach is investigated theoretically in the mean-field limit. We establish a computable and provable bound on the difference in the cost functional for MPC controlled and optimal controlled system dynamics in the mean-field limit. The result of the present work extends previous findings for systems of ordinary differential equations. Numerical results in the mean-field setting are given.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Nov 2015.
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Citing papers per year: 2023: 2.
2 papers.
- 2023On kernel-based statistical learning in the mean field limit27 Oct 2023
- 2023Reproducing kernel Hilbert spaces in the mean field limit28 Feb 2023