Stability and Convergence of a Randomized Model Predictive Control Strategy - Veldman, Daniel; Borkowski, Alexandra; Zuazua, Enrique (IEEE Transactions on Automatic Control, 2024)
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.
CRIS-Team Scopus Importer:2024-03-22
Keywords: Approximation algorithms; Computational efficiency; Convergence; Error Estimates; Model Predictive Control; Numerical stability; Random Batch Method; Read only memory; Receding Horizon Control; Stability; Stability criteria; Vectors