Fuzzy uncertainty in forward dynamics simulation

Journal article
(Original article)


Publication Details

Author(s): Eisentraudt M, Leyendecker S
Journal: Mechanical Systems and Signal Processing
Publication year: 2018
Volume: 126
Pages range: 590-608
ISSN: 0888-3270


Abstract

In this paper, fuzzy uncertainty in forward dynamics simulation is considered. The output of the dynamical system – a fuzzy function – is determined on the basis of α" role="presentation" style="display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">α-discretisation together with α" role="presentation" style="display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">α-level optimisation. A new method for an efficient realisation of α" role="presentation" style="display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">α-level optimisation is developed, which is applicable to arbitrary time integration schemes. The method, called ‘Graph Follower’, is based on combinations of local optimisations and time integration steps. Different formulations of the underlying α" role="presentation" style="display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">α-level optimisation problem are derived and examined. In particular, an approximative description of the output as a function of the parameters is introduced, which enables a significant reduction of the numerical complexity of the developed method.


FAU Authors / FAU Editors

Eisentraudt, Markus
Chair of Applied Dynamics
Leyendecker, Sigrid Prof. Dr.-Ing.
Chair of Applied Dynamics


Research Fields

structure preserving simulation and optimal control
Chair of Applied Dynamics
Modellierung/Simulation/Optimierung
Research focus area of a faculty: Technische Fakultät


How to cite

APA:
Eisentraudt, M., & Leyendecker, S. (2018). Fuzzy uncertainty in forward dynamics simulation. Mechanical Systems and Signal Processing, 126, 590-608. https://dx.doi.org/10.1016/j.ymssp.2019.02.036

MLA:
Eisentraudt, Markus, and Sigrid Leyendecker. "Fuzzy uncertainty in forward dynamics simulation." Mechanical Systems and Signal Processing 126 (2018): 590-608.

BibTeX: 

Last updated on 2019-21-03 at 14:10