DocumentCode :
3642860
Title :
Modeling of an accelerometer-based inclinometer by artificial neural networks
Author :
Ahmet Kırlı;Doğan Aydeniz;Vasfi Emre Ömürlü
Author_Institution :
Mechatronic Engineering Department, Yildiz Technical University, A309 Istanbul, 34349 Turkiye
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
785
Lastpage :
790
Abstract :
In this study, dynamic modeling of an accelerometer based inclinometer is carried out. Empirical methods are used in order to obtain the model of the system and an experimental setup is designed and constructed to realize the required experiments. Classical system identification and neural network methods are used to acquire the dynamic models. Since, accelerometers/inclinometers are commonly used in spatially moving vehicles; simulation models of these are needed. Taking advantage of this dynamic model, the simulation results, which include accelerometers/inclinometers, can become more realistic and extensive filtering techniques would work more efficiently with better sub-system models.
Keywords :
"Artificial neural networks","System identification","Data models","Atmospheric modeling","Vehicles","DC motors","Trajectory"
Publisher :
ieee
Conference_Titel :
Mechatronics (ICM), 2011 IEEE International Conference on
Print_ISBN :
978-1-61284-982-9
Type :
conf
DOI :
10.1109/ICMECH.2011.5971221
Filename :
5971221
Link To Document :
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