4th International Conference on Automatic Control and Mechatronic Engineering (ICACME 2015)

29-30 May 2015
Kuala Lumpur, Malaysia

Past Events

4th International Conference on Automatic Control and Mechatronic Engineering (ICACME 2015) - 29-30 May 2015, Kuala Lumpur, Malaysia (44364)
3rd International Conference on Automatic Control and Mechatronic Engineering (ICACME 2014) - 13-14 Jun 2014, Xiamen SeaShine Hotel Palace, China (38030)
International Conference on Automatic Control and Mechatronic Engineering (ICACME) 2026

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Science: Engineering, Physics
Technology: Materials, Nanotechnology, Robotics

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    Mustafa RasemAbuzeid1

     Nasr E Shtawa2

    1Aljabal Algharbi University, Faculty of Engineering - Gharian, Dept. Of Electrical Eng.

    2University of Tripoli, Faculty of Engineering,  Dept. of Electrical Eng.


    Abstract 

    This paper presents the most commonly used controller in the industry field is the (PID) controller. Fuzzy logic controller (FLC) provides an alternative to PID controller. The purpose of this paper is to design a Fuzzy Logic controller to improve the performance (speed) of the DC motor in order to control the angular speed of the motor. The purpose of Fuzzy Logic controller is to improve the performance of DC motor by controlling the speed of the motor using different system and to show that the Fuzzy Logic controller can be used on the DC motor control.

    1-Introduction  

    The speed of DC motor can be adjusted to a great extent so as to provide easy control and high performance. There are several conventional and numeric controller types intended for controlling the DC motor speed at its executing various tasks, PID Controller, Fuzzy Logic Controller [1]. The terms fuzzy logic is used with a number of deferent meanings. Fuzzy logic has been successfully applied to many control problems, more than any other areas of applications. Various fuzzy programming tools have been developed to facilitate fuzzy rule of control. Fuzzy logic developed by Zadech is applied for controller design in many applications. A fuzzy logic controller (FLC) was proved analytically to be equivalent to a nonlinear PI controller when a nonlinear defuzzification method is used. The result from the comparisons of conventional and

    fuzzy logic controller techniques in the form of FLC and fuzzy compensator also showed fuzzy logic can reduce the effects of nonlinearity in a DC motor and improve the performance of a controller [2].