000			02698ntm a2200241 a 4500
001			vtls000083919
003			KUKTEM
005			20251117113235.0
008			141120t2013 my a f m 000 0 eng d
020			_aTHE0005635(Local)
039		9	_a201905171204 _bhanafiah _c201411210922 _dariffin _y201411201702 _zariffin
040			_aUMP
090			_aTA355 .Z85 2013 r Bc.
100	0		_aMuhammad Zulhilmi Zakaria
245	1	0	_aVibration control of single link flexible manipulator by using neural network / _cMuhammad Zulhilmi Zakaria
260			_aKuantan, Pahang : _bUMP, _c2013
300			_axvi, 71 p. : _bill. ; _c30 cm. + _e1 CD-ROM
502			_aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2013
504			_aBibliography : p. 70-71
520	3		_aThis project presents simulation on minimizing vibration error in single link flexible manipulator system by using neural network system. Flexible manipulator system has a flexible link, an actuator-gear mechanism to rotate the link, an optical encoder to measure joint rotation, accelerometers and strain gauges to sense flexible motion, an optical arrangement to measure the endpoint position and an occasional force sensor attached to the end-point. The overall aim of this project is to develop a dynamic modeling and controller for single link flexible manipulator. In spite of it, we need to minimize the vibration using neural network controller in single link flexible manipulator. The vibration error that occurs in the flexible manipulator is needed to be study and try to reduce it by using the controller (neural network). Towards this thesis, the single link flexible manipulator system being minimize the error by using intelligent neural network controller, and be compared with system existing controller (PID) and the system without controller so that we can see the clearly error percentage reduced. In order to achieve the objective for this project, mathematical model will develop based on system identification using different method such as Lagrage method, Euler-Beurnoulli and System Identification Toolbox in MATLAB and implement it in Mathlab simulink. The results that we achieved is the neural network give the best in order to minimize the vibration error compared to the system without controller about 60% reduction of error and 10% of reduction of error when compared with system with PID controller. Conclusively, the intelligent neural network give us the better results and followed the characteristic of single link flexible manipulator as we desired.
650		0	_aVibration
999			_aVIRTUA40 _c5281 _d5287
999			_aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992