Computational approaches for mixed integer optimal control problems with indicator constraints

Optimal control problems with mixed integer control functions and logical implications, such as a state-dependent restriction on when a control can be chosen (so-called indicator or vanishing constraints) frequently arise in practice. A prominent example is the optimal cruise control of a truck. As...

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Hauptverfasser: Jung, Michael (VerfasserIn) , Kirches, Christian (VerfasserIn) , Sager, Sebastian (VerfasserIn) , Sass, Susanne (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 5 October 2018
In: Vietnam journal of mathematics
Year: 2018, Jahrgang: 46, Heft: 4, Pages: 1023-1051
ISSN:2305-2228
DOI:10.1007/s10013-018-0313-z
Online-Zugang:Verlag, Volltext: https://doi.org/10.1007/s10013-018-0313-z
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Verfasserangaben:Michael N. Jung, Christian Kirches, Sebastian Sager, Susanne Sass
Beschreibung
Zusammenfassung:Optimal control problems with mixed integer control functions and logical implications, such as a state-dependent restriction on when a control can be chosen (so-called indicator or vanishing constraints) frequently arise in practice. A prominent example is the optimal cruise control of a truck. As every driver knows, admissible gear choices critically depend on the current velocity. A large variety of approaches has been proposed on how to numerically solve this challenging class of control problems. We present a computational study in which the most relevant of them are compared for a reference model problem, based on the same discretization of the differential equations. This comprehends dynamic programming, implicit formulations of the switching decisions, and a number of explicit reformulations, including mathematical programs with vanishing constraints in function spaces. We survey all of these approaches in a general manner, where several formulations have not been reported in the literature before. We apply them to a benchmark truck cruise control problem and discuss advantages and disadvantages with respect to optimality, feasibility, and stability of the algorithmic procedure, as well as computation time.
Beschreibung:Gesehen am 07.11.2019
Beschreibung:Online Resource
ISSN:2305-2228
DOI:10.1007/s10013-018-0313-z