Abstract
The development of
automatic control processes has played a vital role in the recent engineering
applications. Nowadays, traditional control techniques such as proportional
integral differential (PID) are very commonly utilized for speed control of
electrical motors. However, it is observed that the classical control
techniques do not have an adequate performance in the case of nonlinear
systems. Because of the simple and continuous control characteristics, the
direct current (DC) motors have been widely used in many industrial
applications such as robotic manipulators, electric vehicles, steel mills,
electric cranes and much more. In this paper, the DC motor speed controller
with an embedded system is designed and the speed of DC motor is controlled
using a fuzzy logic control (FLC) technique. The controller-based on FLC is
investigated with the help of Matlab/Simulink package program. Firstly, the
controller is simulated and designed using the Proteus program and then it is
implemented with the embedded system using Arduino. The results show that FLC can be successfully
used to control the speed of the DC motor with an embedded system.
References
- Ali, N. I. (2013). Simulation for position control of DC motor using fuzzy logic controller. Universiti Tun Hussein Onn Malaysia, Moyer, E., & Chicago, U. (2010). Basics on electricity and electrical generation. The University of Chicago. Nasira, G., Kumar, S. A., & Kiruba, M. S. (2008). A comparative study of fuzzy logic with artificial neural networks algorithms in clustering. Journal of Computer Applications, 1(4), 6. Rai, J., Singhal, M., & Nandwani, M. (2012). Speed control of DC motor using fuzzy logic technique. IOSR Journal of Electrical and Electronics Engineering, 3(6), 41-48. Suman, S. K., & Giri, V. K. (2016). Investigation and Implementation of Genetic Algorithm for Speed Control of DC Motor Based on PID Controller. Journal of Engineering and Applied Sciences, 100(6), 1428-1433.
Abstract
The development of
automatic control processes has played a vital role in the recent engineering
applications. Nowadays, traditional control techniques such as proportional
integral differential (PID) are very commonly utilized for speed control of
electrical motors. However, it is observed that the classical control
techniques do not have an adequate performance in the case of nonlinear
systems. Because of the simple and continuous control characteristics, the
direct current (DC) motors have been widely used in many industrial
applications such as robotic manipulators, electric vehicles, steel mills,
electric cranes and much more. In this paper, the DC motor speed controller
with an embedded system is designed and the speed of DC motor is controlled
using a fuzzy logic control (FLC) technique. The controller-based on FLC is
investigated with the help of Matlab/Simulink package program. Firstly, the
controller is simulated and designed using the Proteus program and then it is
implemented with the embedded system using Arduino. The results show that FLC can be successfully
used to control the speed of the DC motor with an embedded system.
References
- Ali, N. I. (2013). Simulation for position control of DC motor using fuzzy logic controller. Universiti Tun Hussein Onn Malaysia, Moyer, E., & Chicago, U. (2010). Basics on electricity and electrical generation. The University of Chicago. Nasira, G., Kumar, S. A., & Kiruba, M. S. (2008). A comparative study of fuzzy logic with artificial neural networks algorithms in clustering. Journal of Computer Applications, 1(4), 6. Rai, J., Singhal, M., & Nandwani, M. (2012). Speed control of DC motor using fuzzy logic technique. IOSR Journal of Electrical and Electronics Engineering, 3(6), 41-48. Suman, S. K., & Giri, V. K. (2016). Investigation and Implementation of Genetic Algorithm for Speed Control of DC Motor Based on PID Controller. Journal of Engineering and Applied Sciences, 100(6), 1428-1433.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | November 30, 2018 |
| Submission Date | August 15, 2018 |
| Published in Issue | Year 2018 Volume: 8 Issue: 2 |
