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Modeling the magneto- rheological damper using recurrent neural network method

Muhammad Afiq Naquiddin, Abd Rahman (2012) Modeling the magneto- rheological damper using recurrent neural network method. Faculty of Mechanical Engineering, Universiti Malaysia Pahang.


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This thesis is study about modeling the Magnetorheological damper using Recurrent Neural Network method. Five different values of current were used in order to modeling the MR damper, which are 0.0 ampere, 0.5 ampere, 1.0 ampere, 1.5 ampere and 2.0 ampere. In order to modeling the MR damper, the graph of simulation damper will be compared with the experimental damper. The results will get the Square Error for the simulation damper. Then, the Root Mean Square Error will be calculated to get the difference between the simulation damper and experimental damper. The results show that the lowest RMSE for the simulation damper were value 0.4008, while the highest RMSE is 1.9882. From the results also, the better current value to modeling the MR damper is using the MR damper with the lowest RMSE.

Item Type: Undergraduates Project Papers
Uncontrolled Keywords: Damping (Mechanics)
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Nik Ahmad Nasyrun Nik Abd Malik
Date Deposited: 06 Jan 2014 03:35
Last Modified: 03 Mar 2015 09:18
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