Differentiable Model Predictive Control on the GPU

ICLROral2026

Authors
Emre Adabag, Marcus Greiff, John Subosits, Thomas Jonathan Lew
Affiliation
University of Michigan - Ann Arbor
Venue
ICLR 2026
Track
Oral

TL;DR

Differentiable model predictive control (MPC) offers a powerful framework for combining learning and control. However, its adoption has been limited by the inherently sequential nature of traditional optimization algorithms, which are challenging to parallelize on modern computing hardware like GPUs.

Opening excerpt from the authors’ abstract. source

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Topics

optimization control

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