Veldman D, Borkowski A, Zuazua E (2024)
Publication Language: English
Publication Type: Journal article
Publication year: 2024
Pages Range: 1-8
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 RBM-MPC of unconstrained linear systems. The obtained estimates are validated in a numerical example that also shows a clear computational advantage of RBM-MPC.
APA:
Veldman, D., Borkowski, A., & Zuazua, E. (2024). Stability and Convergence of a Randomized Model Predictive Control Strategy. IEEE Transactions on Automatic Control, 1-8. https://doi.org/10.1109/TAC.2024.3375253
MLA:
Veldman, Daniel, Alexandra Borkowski, and Enrique Zuazua. "Stability and Convergence of a Randomized Model Predictive Control Strategy." IEEE Transactions on Automatic Control (2024): 1-8.
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