Performance comparision of self-tuning PID controller for controlling the speed of a DC motor
DC motors are widely used in industrial applications, such as electric trains, robot manipulators and home appliances where speed and position control of the motor are required. The DC motors have high primary torque that makes it suitable in many applications. Moreover, the DC motors have the advan...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/22478/1/Performance%20Comparision%20Of%20Self-Tuning%20PID%20Controller%20For%20Controlling%20The%20Speed%20Of%20A%20DC%20Motor.pdf http://eprints.utem.edu.my/id/eprint/22478/2/Performance%20comparision%20of%20self-tuning%20PID%20controller%20for%20controlling%20the%20speed%20of%20a%20DC%20motor.pdf |
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| Summary: | DC motors are widely used in industrial applications, such as electric trains, robot manipulators and home appliances where speed and position control of the motor are required. The DC motors have high primary torque that makes it suitable in many applications. Moreover, the DC motors have the advantage of implementing in a wide range of operating speed, such as above or below the rated speed. In addition the control system of the DC motor is simple, flexible and low cost when compared to other types of motors. In industrial applications the speed control system that able to give a fast response with a minimum overshoot, lower steady state error, shorter settling time and faster rising time are essential. The speed control of the DC motor is fed through a buck-converter. The buck converter will regulate the desired output voltage level and maintain the speed of the DC motor constant. Any change in torque does not affect the speed of the motor. Therefore, in this thesis, the DC motor speed control by using three different types of controller are being analyzed and developed. The controller gains are obtained based on conventional PID, self-tuning fuzzy logic and self-tuning genetic algorithm (GA) controller. The performance evaluation of the system is developed based on the MA TLAB/Simulink. Results are investigated considering the system running with no load and half load at 500 and 1000 rpm. The results demonstrate that the proposed GA tuned PIO provides improved performance as compared to PIO controller and fuzzy logic tuned PIO controller in terms of time specification such as 0% overshoot, shorter settling time, faster rise time and zero steady state error. |
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