02974ntm a2200265 a 4500001001400000003000700014005001700021008004100038020002200079039007300101040000800174090002600182100003000208245011100238260003400349300004500383502009200428504002800520520179200548650001402340952012002354952013202474999002502606999007702631vtls000083919KUKTEM20251117113235.0141120t2013    my a   f m    000 0 eng d  aTHE0005635(Local) 9a201905171204bhanafiahc201411210922dariffiny201411201702zariffin  aUMP  aTA355 .Z85 2013 r Bc.0 aMuhammad Zulhilmi Zakaria10aVibration control of single link flexible manipulator by using neural network /cMuhammad Zulhilmi Zakaria  aKuantan, Pahang :bUMP,c2013  axvi, 71 p. :bill. ;c30 cm. +e1 CD-ROM  aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2013  aBibliography : p. 70-713 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. 0aVibration  00104071a20000b20000d2019-09-04l0oTA355 .Z85 2013 r Bc.p0000086228r2019-09-04 00:00:00t1w2019-09-04yPSM  00104070a20000b20000d2019-09-04l0oCD 8055 | TA355 .Z85 2013 r Bc.p0000086229r2019-09-04 00:00:00t1w2019-09-04yACCOM  aVIRTUA40c5281d5287  aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992