Suboptimal nonlinear model predictive control with input move-blocking

DOI10.1080/00207179.2022.2152381arXiv2109.12355OpenAlexW3204220758MaRDI QIDQ6378567

Torsten Bertram, Artemi Makarow, Christoph Rösmann

Publication date: 25 September 2021

Abstract: This paper deals with the integration of input move-blocking into the framework of suboptimal model predictive control. The blocked input parameterization is explicitly considered as a source of suboptimality. A straightforward integration approach is to hold back a manually generated stabilizing fallback solution in some buffer for the case that the optimizer does not find a better input move-blocked solution. An extended approach superimposes the manually generated stabilizing warm-start by the move-blocked control sequence and enables a stepwise improvement of the control performance. In addition, this contribution provides a detailed review of the literature on input move-blocked model predictive control and combines important results with the findings of suboptimal model predictive control. A numerical example supports the theoretical results and shows the effectiveness of the proposed approach.

Full work available at URL: https://doi.org/10.1080/00207179.2022.2152381

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Asymptotic stability in control theory (93D20) Model predictive control (93B45)