Stability and Convergence of a Randomized Model Predictive Control Strategy

Daniël Veldman; Alexandra Borkowski; Enrique Zuazua

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arXiv · 2211.05463

Stability and Convergence of a Randomized Model Predictive Control Strategy

Daniël Veldman·Alexandra Borkowski·Enrique Zuazua

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Abstract

RBM-MPC is a computationally efficient variant of Model Predictive Control (MPC) in which the Random Batch Method (RBM) is used to speed up the finite-horizon optimal control problems at each iteration. In this paper, stability and convergence estimates are derived for RBMMPC of unconstrained linear systems. The obtained estimates are validated in a numerical example that also shows a clear computational advantage of RBM-MPC.

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Daniël Veldman, Alexandra Borkowski, Enrique Zuazua. 2022-11-10. Stability and Convergence of a Randomized Model Predictive Control Strategy. https://arxiv.org/abs/2211.05463

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