Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/68384
Title: Mixed-integer optimal control under minimum dwell time constraints
Author(s): Zeile, ClemensLook up in the Integrated Authority File of the German National Library
Robuschi, Nicolò
Sager, SebastianLook up in the Integrated Authority File of the German National Library
Issue Date: 2021
Type: Article
Language: English
URN: urn:nbn:de:gbv:ma9:1-1981185920-703353
Subjects: Mixed-integer linear programming
Mixed-integer linear programming
Optimal control
Discrete approximations ·
Switched dynamic systems
Approximation methods and heuristics
Minimum dwell time constraints
Abstract: Tailored Mixed-Integer Optimal Control policies for real-world applications usually have to avoid very short successive changes of the active integer control. Minimum dwell time (MDT) constraints express this requirement and can be included into the combinatorial integral approximation decomposition, which solves mixed-integer optimal control problems (MIOCPs) to ε-optimality by solving one continuous nonlinear program and one mixed-integer linear program (MILP). Within this work, we analyze the integrality gap of MIOCPs under MDT constraints by providing tight upper bounds on the MILP subproblem. We suggest different rounding schemes for constructing MDT feasible control solutions, e.g., we propose a modification of Sum Up Rounding. A numerical study supplements the theoretical results and compares objective values of integer feasible and relaxed solutions.
URI: https://opendata.uni-halle.de//handle/1981185920/70335
http://dx.doi.org/10.25673/68384
Open Access: Open access publication
License: (CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0(CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0
Sponsor/Funder: Projekt DEAL 2020
Journal Title: Mathematical programming
Publisher: Springer
Publisher Place: Berlin
Volume: 188
Original Publication: 10.1007/s10107-020-01533-
Page Start: 653
Page End: 694
Appears in Collections:Fakultät für Mathematik (OA)

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