| 000 | 01782nam a2200265 a 4500 | ||
|---|---|---|---|
| 001 | vtls000075887 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204550.0 | ||
| 008 | 131107t2012 my da f m 000 0 eng d | ||
| 020 | _aTHE0005510(Local) | ||
| 039 | 9 |
_a201905160955 _bhanafiah _c201311131646 _dnabilah _y201311071238 _znabilah |
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| 040 | _aUMP | ||
| 090 | _aQC189.5 .R53 2012 rs Bc. | ||
| 100 | 0 | _aMohd Ridzwan Ramli | |
| 245 | 1 | 0 |
_aModeling magneto-rheological damper using ANFIS method / _cMohd Ridzwan Hj Ramli |
| 260 |
_aKuantan, Pahang : _bUMP, _c2012 |
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| 300 |
_axvi, 53 p. : _bill. ; _c30 cm. + _e1 CD-ROM |
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| 502 | _aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang – 2012 | ||
| 504 | _aBibliography : p. 48-50 | ||
| 520 | 3 | _aThis thesis focused on the development Modeling Magneto-Rheological damper using Adaptive Neuro-Fuzzy Inference System (ANFIS) method. Magneto-Rheological (MR) damper is a semi-active control device and has been characterized by a set of nonlinear differential equations which represent a model of the MR damper. By using this mathematical model, the force of the MR damper is directly solved to a given displacement and applied current. However, solving the non-linear equations describing the performance of the MR damper may be difficult or time consuming to predict a required voltage. One of the methods to model the MR damper is using (ANFIS).It is faster than the mathematical model for keeping the error small. ANFIS has been effectively applied to model complex systems because of its great training process. | |
| 650 | 0 | _aMagnetic suspension | |
| 650 | 0 | _aDamping (Mechanics) | |
| 650 | 0 | _aFuzzy sets | |
| 999 |
_aVIRTUA40 _c4219 _d4225 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992 | ||