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2009

Verlässlichkeit im aktiven selbstoptimierenden Spurführungsmodul eines schienengebundenen Fahrzeugs

Sondermann-Wölke, C., Geisler, J., Hirsch, M., & Hemsel, T. (2009). Verlässlichkeit im aktiven selbstoptimierenden Spurführungsmodul eines schienengebundenen Fahrzeugs. In J. Gausemeier, Rammig, F. J., Schäfer, W., & Trächtler, A. (Hrsg.), Entwurf mechatronischer Systeme (Bd. 250). Paderborn: HNI-Verlagsschriftenreihe. (Original work published 04/2009)
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Geisler, Jens
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2009

Book Chapter

Christoph Sondermann-Wölke

Jens Geisler

M. Hirsch

T. Hemsel

J. Gausemeier

F. Rammig

W. Schäfer

A. Trächtler

2008

The active guidance module of a rail-bound vehicle as an application of dependability oriented design in self-optimizing systems

Sondermann-Wölke, C., Geisler, J., Müller, T., Trächtler, A., & Böcker, J. (2008). The active guidance module of a rail-bound vehicle as an application of dependability oriented design in self-optimizing systems. In Proceedings of the ASME 2008 - International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE). New York. (Original work published 08/2008)
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Geisler, Jens
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2008

Conference Paper

Christoph Sondermann-Wölke

Jens Geisler

T. Müller

A. Trächtler

J. Böcker
Multiobjective Optimization of Control Trajectories for the Guidance of a Rail-Bound Vehicle

Geisler, J., Witting, K., Trächtler, A., & Dellnitz, M. (2008). Multiobjective Optimization of Control Trajectories for the Guidance of a Rail-Bound Vehicle. In Proceedings of the 17th IFAC World Congress. Seoul, Korea. http://doi.org/10.3182/20080706-5-KR-1001.00738 (Original work published 07/2008)

Abstract

Self-optimization refers to the ability of a mechatronic system to autonomously adapt the way it performs its functions to changing environmental and operational conditions or user demands. In this work we propose to use multiobjective optimal control to enable the self-optimization of the guidance of a rail-bound vehicle. We consider different strategies to reduce the computational cost of the optimization. Most importantly, a two-degree-of-freedom controller is used to separate optimal trajectory generation from disturbance compensation. Also, in order to solve the multiobjective optimization problem, an approximation of the entire set of optimal compromises of the objectives, the so-called Pareto set, is computed offline at design time. From this, we can derive a collection of weighting vectors that capture the best trade-off between the objectives for different situations. Given this set of preselected weights, for the online optimization, the objective function can be taken to be a weighted sum that best matches the situation at hand. For the guidance system we consider three objectives. Preliminary offline simulation results are presented.
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Geisler, Jens
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2008

Conference Paper

Jens Geisler

K. Witting

A. Trächtler

M. Dellnitz
Self-Optimization of the Guidance Module of a Rail-bound Vehicle

Geisler, J., Witting, K., Trächtler, A., & Dellnitz, M. (2008). Self-Optimization of the Guidance Module of a Rail-bound Vehicle. In Self-optimizing Mechatronic Systems: Designing the Future (7th International Heinz Nixdorf Symposium). Paderborn: HNI-Verlagsschriftenreihe. Abgerufen von https://www.hni.uni-paderborn.de/pub/5674 (Original work published 02/2008)
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Geisler, Jens
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2008

Conference Paper

Jens Geisler

K. Witting

A. Trächtler

M. Dellnitz

Publikationen

2009

Verlässlichkeit im aktiven selbstoptimierenden Spurführungsmodul eines schienengebundenen Fahrzeugs

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2008

The active guidance module of a rail-bound vehicle as an application of dependability oriented design in self-optimizing systems

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Multiobjective Optimization of Control Trajectories for the Guidance of a Rail-Bound Vehicle

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Self-Optimization of the Guidance Module of a Rail-bound Vehicle

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