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040 _aUMP
090 _aTK7872.P76 N56 2009 rs Bc.
100 0 _aNina Naisha Suhaimi
245 1 0 _aImplementation of fuzzy logic controller on revolute control universal stretch & bending machine (USBM) /
_cNina Naisha Binti Suhaimi
260 _aKuantan, Pahang :
_bUMP,
_c2009
300 _a108 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 computer disc
502 _aProject paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2009
520 3 _aMotor speed control is very important in rotating machinery applications. There are many applications that have been developed based on motor speed control theory such as to run the machines at most factory automation industry as well known the machines are easiest to damage without controller. The speed control of motor is very difficult to be implemented by using conventional control techniques, as it requires a very complex mathematical model. The purpose of this project is to describe the research of fuzzy logic controller (FLC) design based on programmable logic controller (PLC) in order to control the speed of the motor. The model of the PLC that has been used in this project is OMRON CJIG-CPU42P where this PLC has a build in loop control that can be made the ladder diagram quite simple using function block in Cx-process tools. In this project, the system without controller shows that is an open loop control. Therefore, when break is applied there is no feedback for the system to increase the voltage in order for the motor to maintain the desired speed output. Compare by using the controller FLC, when the breaking is applied there is a feedback for the system to increase the voltage to get the desired output that the user need. From this hardware implementation there are five rules that have been used which is five membership functions with trapezoid and triangular shape. Analysis will be done and it shows that the triangular shape is much better compare to the trapezoid shape and without controller in the system. Before the controller will be implementing in the PLC, the simulations were done using MATLAB fuzzy logic toolbox and SIMULINK. The objective of the simulation is to predict the system response of the motor in with or without controller.
650 0 _aFuzzy logic
650 0 _aProgrammable logic controllers
999 _aVIRTUA40
_c2262
_d2268
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5200*6500*6501*9992