IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 1 Ver. III (Jan – Feb. 2015), PP 37-47 www.iosrjournals.org DOI: 10.9790/1676-10133747 www.iosrjournals.org 37 | Page DC Motor Position Control Using Fuzzy Proportional-Derivative Controllers With Different Defuzzification Methods 1 Shravan Kumar Yadav 1 Shravan Kumar Yadav has done B.Tech. degree program in Electrical & Electronics Engineering(EEE) at Apex Institute of Technology & Management , Bhubaneswar , India. . Abstract: A fuzzy control system to control the position of a DC motor. The motor was modelled and converted to a subsystem in Simulink. First, a crisp proportional-derivative (PD) controller was designed and tuned using a Simulink block instead of conventional tuning methods such as hand-tuning or Ziegler-Nichols frequency response method. Then a fuzzy proportional-derivative (FPD) controller was designed and system responses of FPDs with different defuzzification methods were investigated. A disturbance signal was also applied to the input of the control system. FPD controller succeeded to reject the disturbance signal without further tuning of the parameters whereby crisp PD controller failed The purpose of this project is to control the position of DC Motor by using Fuzzy Logic Controller (FLC) with MATLAB application. The scope includes the simulation and modelling of DC motor, fuzzy controller and conventional PID controller as benchmark to the performance of fuzzy system. The position control is an adaptation of Closed Circuit Television (CCTV) system. Fuzzy Logic control can play important role because knowledge based design rules can be easily implemented in the system with unknown structure and it is going to be popular since the control design strategy is simple and practical. This make FLC an alternative method to the conventional PID control method used in nonlinear industrial system. The results obtained from FLC are compared with PID control for the dynamic response of the closed loop system. Parameters such as peak position in degree, settling time in second and maximum overshoot in percent will be part of the simulation result.. Keywords: DC motor, Fuzzy logic control, defuzzification, PI controllers, PID controllers I. Introduction Because of their high reliabilities, flexibilities and low costs, DC motors are widely used in industrial applications, robot manipulators and home appliances where speed and position control of motor are required. PID controllers are commonly used for motor control applications because of their simple structures and intui- tionally comprehensible control algorithms. Controller parameters are generally tuned using hand-tuning or Ziegler-Nichols frequency response method. Both of these methods have successful results but long time and effort are required to obtain a satisfactory system. Two main problems encountered in motor control are the time-varying nature of motor parameters under operating conditions and existence of noise in system loop. Analysis and control of complex, nonlinear and/or time-varying systems is a challenging task using conventional methods because of uncertainties. Fuzzy set theory (Zadeh, 1965) which led to a new control me- thod called Fuzzy Control which is able to cope with system uncertainties. One of the most important advantag- es of fuzzy control is that it can be successfully applied to control nonlinear complex systems using an operator experiences or control engineering knowledge without any mathematical model of the plant (Assilian, 1974), (Kickert, 1976). DC motor control is generally realized by adjusting the terminal voltage applied to the arma- ture but other methods such as adjusting the field resistance, inserting a resistor in series with the armature cir- cuit are also available (Chapman, 2005). Ziegler-Nichols frequency response method is usually used to adjust the parameters of the PID control- lers. However, it is needed to get the system into the oscillation mode to realize the tuning procedure. But it’s not always possible to get most of the technological plants into oscillation. The proposed approach uses both fuzzy controllers and response optimization method to obtain the approximate values of the controller parame- ters. Then the parameters may be slightly varied to obtain the user-defined performance of the real-time control system. Thus, it’s an actual problem to design adaptive PID controllers without getting the system into the osci l- lation mode. In the next section, the mathematical model of a dc motor is used to obtain a transfer function be- tween shaft position and applied armature voltage. This model is then built in MATLAB Simulink, design and tuning of proportional-integral-derivative (PID) controllers are reviewed and a crisp PD control system is de- signed in Simulink with the proposed design procedure, it’s mentioned about the fuzzy logic controller design issues and a fuzzy proportional-derivative controller is designed with the proposed approach. Some of the com- monly used defuzzification methods are discussed and system responses with different defuzzification methods are compared. Finally disturbance rejection capabilities of the designed controllers are investigated.