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On Piecewise Quadratic Terminal Costs for MPC
Abstract
This paper presents a novel approach to synthesize stabilizing termi- nal ingredients for linear model predictive control (MPC) schemes, with the aim of increasing the region of attraction while reducing suboptimal- ity with respect to the solution of the infinite-horizon optimal control problem. It is based on the construction of a novel terminal region using methods from the field of configuration-constrained polytopic computing, along with a terminal cost that is exactly equal to the infinite-horizon linear-quadratic regulator cost in a nontrivial neighborhood of the steady- state. The practical performance of the controller is illustrated through various case studies, and comparisons with state-of-the-art approaches are presented.
Versions
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BibTeX
@misc{mulagaleti2026piecewise,
title = {{On Piecewise Quadratic Terminal Costs for MPC}},
author = {Sampath Kumar Mulagaleti and Boris Houska and Mario Zanon and Mario E. Villanueva},
howpublished = {arXiv},
year = {2026},
month = may,
doi = {10.48550/arxiv.2605.18510},
eprint = {2605.18510},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.18510},
}
RIS
TY - UNPB
TI - On Piecewise Quadratic Terminal Costs for MPC
AU - Sampath Kumar Mulagaleti
AU - Boris Houska
AU - Mario Zanon
AU - Mario E. Villanueva
PY - 2026
DA - 2026/05/18
PB - arXiv
DO - 10.48550/arxiv.2605.18510
UR - https://arxiv.org/abs/2605.18510
AB - This paper presents a novel approach to synthesize stabilizing termi- nal ingredients for linear model predictive control (MPC) schemes, with the aim of increasing the region of attraction while reducing suboptimal- ity with respect to the solution of the infinite-horizon optimal control problem. It is based on the construction of a novel terminal region using methods from the field of configuration-constrained polytopic computing, along with a terminal cost that is exactly equal to the infinite-horizon linear-quadratic regulator cost in a nontrivial neighborhood of the steady- state. The practical performance of the controller is illustrated through various case studies, and comparisons with state-of-the-art approaches are presented.
ER -