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| 003 | EG-GiCUC | ||
| 005 | 20250223031242.0 | ||
| 008 | 150625s2014 ua d f m 000 0 eng d | ||
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_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.13.07.M.Sc.2014.Ah.P | ||
| 100 | 0 | _aAhmed Abdelhaleem Mohammed Salem | |
| 245 | 1 | 0 |
_aPID controller based on artificial intelligence : _bApplied to different models / _cAhmed Abdelhaleem Mohammed Salem ; Supervised Mohamed A. M. Hassan , Mohamed E. Ammar |
| 246 | 1 | 5 |
_aالمتحكم التناسبي التكاملي التفاضلي المعتمد علي الذكاء الإصطناعي : _bمع التطبيق علي نماذج مختلفة |
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_aCairo : _bAhmed Abdelhaleem Mohammed Salem , _c2014 |
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_a138 P. : _bcharts ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines | ||
| 520 | _aThe PID controllers are the most commonly used controller structures in industry. The main challenge is in the aspect of tuning of the gains. There are several traditional techniques introduced by Ziegler and Nichols but it is inefficient. In this thesis, it is proposed that the PID controller tuned based on the Artificial Intelligence techniques (the GAs, the Improved Genetic Algorithms and finally the PSO). Then applied all techniques to different applications (DC-Motor and AVR System), from the results the techniques based on Artificial intelligence are better than traditional techniques | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aAVR system | |
| 653 | 4 | _aDC-Motor | |
| 653 | 4 | _aPID-controller | |
| 700 | 0 |
_aMohamed Ahmed Moustafa Hassan , _eSupervisor |
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| 700 | 0 |
_aMohammed Elsayed Ammar , _eSupervisor |
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| 856 | _uhttp://172.23.153.220/th.pdf | ||
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_aEnas _eCataloger |
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| 905 |
_aNazla _eRevisor |
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_2ddc _cTH |
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_c51432 _d51432 |
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