Abdullah Cakan

PhD, Visiting Scholar



Contact

Abdullah Cakan


[email protected], [email protected]


Mechanical Engineering, Konya Technical University

Industrial and Systems Engineering, Virginia Tech




Abdullah Cakan

PhD, Visiting Scholar


[email protected], [email protected]


Mechanical Engineering, Konya Technical University

Industrial and Systems Engineering, Virginia Tech



Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor


Journal article


Eka Suci Rahayu, A. Ma’arif, Abdullah Çakan
International Journal of Robotics and Control Systems, 2022

Semantic Scholar DOI
Cite

Cite

APA   Click to copy
Rahayu, E. S., Ma’arif, A., & Çakan, A. (2022). Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor. International Journal of Robotics and Control Systems.


Chicago/Turabian   Click to copy
Rahayu, Eka Suci, A. Ma’arif, and Abdullah Çakan. “Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor.” International Journal of Robotics and Control Systems (2022).


MLA   Click to copy
Rahayu, Eka Suci, et al. “Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor.” International Journal of Robotics and Control Systems, 2022.


BibTeX   Click to copy

@article{eka2022a,
  title = {Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor},
  year = {2022},
  journal = {International Journal of Robotics and Control Systems},
  author = {Rahayu, Eka Suci and Ma’arif, A. and Çakan, Abdullah}
}

Abstract

The use of DC motors is now common because of its advantages and has become an important necessity in helping human activities. Generally, motor control is designed with PID control. The main problem that is often discussed in PID is parameter tuning, namely determining the value of the Kp, Ki, and Kd parameters in order to obtain optimal system performance. In this study, one method for tuning PID parameters on a DC motor will be used, namely the Particle Swarm Optimization (PSO) method. Parameter optimization using the PSO method has stable results compared to other methods. The results of tuning the PID controller parameters using the PSO method on the MATLAB Simulink obtained optimal results where the value of Kp = 8.9099, K = 2.1469, and Kd = 0.31952 with the value of rise time of 0.0740, settling time of 0.1361 and overshoot of 0. Then the results of hardware testing by entering the PID value in the Arduino IDE software produce a stable motor speed response where Kp = 1.4551, Ki= 1.3079, and Kd = 0.80271 with a rise time value of 4.3296, settling time of 7.3333 and overshoot of 1.





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