A Warm-Start Strategy in Interior Point Methods for Shrinking Horizon Model Predictive Control With Variable Discretization StepDownload PDFOpen Website

Published: 01 Jan 2023, Last Modified: 05 Nov 2023IEEE Trans. Autom. Control. 2023Readers: Everyone
Abstract: In this article, we present a warm-start point algorithm in interior point methods for shrinking horizon model predictive control with a variable discretization step. In the algorithm, a convex combination of components of the earlier optimal solution is used to construct an interpolation point, and we use the convex combination of the modified interpolation point and the cold-start point to obtain a warm-start point. We prove that the worst-case iteration complexity of our strategy is better than that of the cold-start. In the numerical experiment of fuel-optimal planetary powered-descent guidance problems, our strategy reduces the number of iterations of second-order cone programming by about 80% with the number of samples available in practical applications.
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