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Research Articles

Suboptimal nonlinear model predictive control with input move-blocking

ORCID Icon, ORCID Icon &
Pages 450-459 | Received 01 Mar 2022, Accepted 17 Nov 2022, Published online: 13 Dec 2022
 

Abstract

This paper deals with the integration of input move-blocking into the framework of suboptimal model predictive control. The blocked input parameterisation is explicitly considered as a source of suboptimality. A straightforward integration approach is to hold back a manually generated stabilising fallback solution in some buffer for the case that the optimiser does not find a better input move-blocked solution. An extended approach superimposes the manually generated stabilising 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.

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