A Gauss–Newton-based decomposition algorithm for Nonlinear Mixed-Integer Optimal Control Problems. (June 2023)

• Record Type: Journal Article
• Authors: Bürger, Adrian; Zeile, Clemens; Altmann-Dieses, Angelika; Sager, Sebastian; Diehl, Moritz
• Is Part Of: Automatica. Volume 152(2023)
• Publication Date: 2023-06
• Subjects: Mixed-integer optimal control -- Switched nonlinear systems -- Algorithms and software; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2023.110967
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: For the fast approximate solution of Mixed-Integer Non-Linear Programs (MINLPs) arising in the context of Mixed-Integer Optimal Control Problems (MIOCPs) a decomposition algorithm exists that solves a sequence of three comparatively less hard subproblems to determine an approximate MINLP solution. In this work, we propose a problem formulation for the second algorithm stage that is a convex approximation of the original MINLP and relies on the Gauss–Newton approximation. We analyze the algorithm in terms of approximation properties and establish a first-order consistency result. Then, we investigate the proposed approach considering a numerical case study of Mixed-Integer Optimal Control (MIOC) of a renewable energy system. The investigation shows that the proposed formulation can yield an improved integer solution regarding the objective of the original MINLP compared with the established Combinatorial Integral Approximation (CIA) algorithm.