Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/35020
Title: | Mixed-integer optimal control under minimum dwell time constraints |
Author(s): | Zeile, Clemens Robuschi, Nicolò Sager, Sebastian |
Issue Date: | 2021 |
Extent: | 1 Online-Ressource (42 Seiten, 858,85 MB) |
Type: | Article |
Language: | English |
Publisher: | Springer Nature, Berlin |
URN: | urn:nbn:de:gbv:ma9:1-1981185920-352228 |
Subjects: | 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 -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/1981185920/35222 http://dx.doi.org/10.25673/35020 |
Open Access: | Open access publication |
License: | (CC BY 4.0) Creative Commons Attribution 4.0 |
Journal Title: | Mathematical programming |
Publisher: | Springer Nature |
Publisher Place: | Berlin |
Issue: | 2020 |
Original Publication: | 10.1007/s10107-020-01533-x |
Page Start: | 653 |
Page End: | 694 |
Appears in Collections: | Fakultät für Mathematik (OA) |
Files in This Item:
File | Description | Size | Format | |
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Sager_et al._Mathematical Programming_2020.pdf | Zweitveröffentlichung | 858.85 kB | Adobe PDF | View/Open |