Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, , 8 - 19, 30.06.2021
https://doi.org/10.29002/asujse.892979

Öz

Kaynakça

  • [1] S. He, L. Liu, X. Hu, J. Xiao, Research on integrated simulation technology of multi-source heterogeneous model based on FMI standard. 13th IEEE Conference on Industrial Electronics and Applications. (2018) 417-422.
  • [2] J. Lopez-Gomez, M.A.D. Vargas-Treviño, S. Vergara-Limon, M. Vargas-Treviño, J. Gutierrez-Gutierrez, A.D. Palomino-Merino, O.G. Felix-Beltran, Influence of PWM torque control frequency in DC motors by means of an optimum design method. IEEE Access. 8 (2020) 80691-80706.
  • [3] N. Saridhar, N. Ramrao, M.K. Singh, PID controller auto tuning using ASBO technique. Journal of Control Engineering and Technology. 4(3) (2014) 192-204.
  • [4] H. Liang, J. Zou, K. Zuo, M.J. Khan, An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system. Mechanical Systems and Signal Processing. 142 (2020) 106708.
  • [5] J. Mendes, L. Osório, R. Araújo, Self-tuning PID controllers in pursuit of plug and play capacity. Control Engineering Practice. 69 (2017) 73-84.
  • [6] P.J. Fleming, R.C. Purshouse, Evolutionary algorithms in control systems engineering: A survey. Control engineering practice. 10(11) (2002) 1223-1241.
  • [7] P. Meshram, R.G. Kanojiya, Tuning of PID controller using Ziegler– Nichols method for speed control of dc motor. IEEE Int. Conf. Adv. Eng., Sci. Manage. (2012) 117–122.
  • [8] S.J. Hammoodi, K.S. Flayyih, A.R. Hamad, Design and implementation speed control system of DC motor based on PID control and matlab simulink. International Journal of Power Electronics and Drive Systems. 11(1) (2020) 127.
  • [9] S. Alqahtani, S. Ganesan, M.A. Zohdy, The Comparison between PI and PID Controllers in Engine Speed Control Model. IEEE International Conference on Electro Information Technology. (2020) 629-634.
  • [10] M.R. Khan, A.A. Khan, U. Ghazali, Speed Control of DC Motor under Varying Load Using PID Controller. International Journal of Engineering. 9(3) (2015) 38-48.
  • [11] A. Parnianifard, A.S. Azfanizam, Metamodel‐based robust simulation‐optimization assisted optimal design of multiloop integer and fractional‐order PID controller. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. 33(1) (2020) e2679.
  • [12] R.D. Muhammad, F. Faisal, Design of Optimal PID Controller For Three Phase Induction Motor Based on Ant Colony Optimization. Sinergi, 24(2) (2020) 125-132.
  • [13] G. Farahani, K. Rahmani, Speed control of a separately excited DC motor using new proposed fuzzy neural algorithm based on FOPID controller. Journal of Control, Automation and Electrical Systems. 30(5) (2019) 728-740.
  • [14] P. Dutta, S.K. Nayak, Grey Wolf Optimizer Based PID Controller for Speed Control of BLDC Motor. Journal of Electrical Engineering & Technology. (2021) 1-7.
  • [15] C. Huang, F. Lei, X. Han, Z. Zhang, Determination of modeling parameters for a brushless DC motor that satisfies the power performance of an electric vehicle. Measurement and Control, 52(7-8) (2019) 765-774.
  • [16] J. Zhang, L. Guo, Theory and design of PID controller for nonlinear uncertain systems. IEEE Control Systems Letters. 3(3) (2019) 643-648.
  • [17] V.Y. Vorobyov, G.V. Sablina, Calculation and Optimization of Parameters of the Discrete PID-controller by the Ziegler-Nichols Method. Automatics & Software Enginery. N1(27) (2019) 7.
  • [18] Y. Dhieb, M. Yaich, A. Guermazi, M. Ghariani, PID controller tuning using ant colony optimization for induction motor. Journal of Electrical Systems. 15(1) (2019) 133-141.
  • [19] R. Singh, B. Bhushan, Improved ant colony optimization for achieving self-balancing and position control for balancer systems. Journal of Ambient Intelligence and Humanized Computing. (2020) 1-18.
  • [20] Y.T. Hsiao, C.L. Chuang, C.C. Chien, Ant colony optimization for designing of PID controllers. IEEE International Conference on Robotics and Automation (2004) 321-326.

Speed Control of DC Motor under Reverse Torque Disturbance with Ant Colony Optimized PID Controller

Yıl 2021, , 8 - 19, 30.06.2021
https://doi.org/10.29002/asujse.892979

Öz

Direct Current (DC) motors are widely used in industrial systems due to their high torque. In ensuring the stability and productivity of a system, it is important that the DC motor within the automation system reaches the reference speed value quickly and its speed remains constant under load. In this study, it is aimed to keep the speed value of DC motor constant under load by optimizing the gain parameters of the Proportional, Integral and Derivative (PID) controller, which is widely used in industrial applications. In the optimization of these parameters, the Ziegler Nichols method (ZNM) and the Ant Colony Optimization method (ACO) were examined comparatively in the simulation environment. PID parameters were determined by open loop responses under the running system with the ZNM. On the other hand, the most optimum solution was obtained among many parameters with the ACO method. Speed control of DC motor was performed with PID controller parameters which are determined according to the best ACO response. Simulation results are presented in comparison with the parameters of settling time, peak time, rising time and response of the system under load. As a result, PID controller run with Kp, Ki, and Kd parameters obtained by ACO algorithm generally gave better results than ZNM.

Kaynakça

  • [1] S. He, L. Liu, X. Hu, J. Xiao, Research on integrated simulation technology of multi-source heterogeneous model based on FMI standard. 13th IEEE Conference on Industrial Electronics and Applications. (2018) 417-422.
  • [2] J. Lopez-Gomez, M.A.D. Vargas-Treviño, S. Vergara-Limon, M. Vargas-Treviño, J. Gutierrez-Gutierrez, A.D. Palomino-Merino, O.G. Felix-Beltran, Influence of PWM torque control frequency in DC motors by means of an optimum design method. IEEE Access. 8 (2020) 80691-80706.
  • [3] N. Saridhar, N. Ramrao, M.K. Singh, PID controller auto tuning using ASBO technique. Journal of Control Engineering and Technology. 4(3) (2014) 192-204.
  • [4] H. Liang, J. Zou, K. Zuo, M.J. Khan, An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system. Mechanical Systems and Signal Processing. 142 (2020) 106708.
  • [5] J. Mendes, L. Osório, R. Araújo, Self-tuning PID controllers in pursuit of plug and play capacity. Control Engineering Practice. 69 (2017) 73-84.
  • [6] P.J. Fleming, R.C. Purshouse, Evolutionary algorithms in control systems engineering: A survey. Control engineering practice. 10(11) (2002) 1223-1241.
  • [7] P. Meshram, R.G. Kanojiya, Tuning of PID controller using Ziegler– Nichols method for speed control of dc motor. IEEE Int. Conf. Adv. Eng., Sci. Manage. (2012) 117–122.
  • [8] S.J. Hammoodi, K.S. Flayyih, A.R. Hamad, Design and implementation speed control system of DC motor based on PID control and matlab simulink. International Journal of Power Electronics and Drive Systems. 11(1) (2020) 127.
  • [9] S. Alqahtani, S. Ganesan, M.A. Zohdy, The Comparison between PI and PID Controllers in Engine Speed Control Model. IEEE International Conference on Electro Information Technology. (2020) 629-634.
  • [10] M.R. Khan, A.A. Khan, U. Ghazali, Speed Control of DC Motor under Varying Load Using PID Controller. International Journal of Engineering. 9(3) (2015) 38-48.
  • [11] A. Parnianifard, A.S. Azfanizam, Metamodel‐based robust simulation‐optimization assisted optimal design of multiloop integer and fractional‐order PID controller. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. 33(1) (2020) e2679.
  • [12] R.D. Muhammad, F. Faisal, Design of Optimal PID Controller For Three Phase Induction Motor Based on Ant Colony Optimization. Sinergi, 24(2) (2020) 125-132.
  • [13] G. Farahani, K. Rahmani, Speed control of a separately excited DC motor using new proposed fuzzy neural algorithm based on FOPID controller. Journal of Control, Automation and Electrical Systems. 30(5) (2019) 728-740.
  • [14] P. Dutta, S.K. Nayak, Grey Wolf Optimizer Based PID Controller for Speed Control of BLDC Motor. Journal of Electrical Engineering & Technology. (2021) 1-7.
  • [15] C. Huang, F. Lei, X. Han, Z. Zhang, Determination of modeling parameters for a brushless DC motor that satisfies the power performance of an electric vehicle. Measurement and Control, 52(7-8) (2019) 765-774.
  • [16] J. Zhang, L. Guo, Theory and design of PID controller for nonlinear uncertain systems. IEEE Control Systems Letters. 3(3) (2019) 643-648.
  • [17] V.Y. Vorobyov, G.V. Sablina, Calculation and Optimization of Parameters of the Discrete PID-controller by the Ziegler-Nichols Method. Automatics & Software Enginery. N1(27) (2019) 7.
  • [18] Y. Dhieb, M. Yaich, A. Guermazi, M. Ghariani, PID controller tuning using ant colony optimization for induction motor. Journal of Electrical Systems. 15(1) (2019) 133-141.
  • [19] R. Singh, B. Bhushan, Improved ant colony optimization for achieving self-balancing and position control for balancer systems. Journal of Ambient Intelligence and Humanized Computing. (2020) 1-18.
  • [20] Y.T. Hsiao, C.L. Chuang, C.C. Chien, Ant colony optimization for designing of PID controllers. IEEE International Conference on Robotics and Automation (2004) 321-326.
Toplam 20 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Ömer Kasım 0000-0003-4021-5412

Yayımlanma Tarihi 30 Haziran 2021
Gönderilme Tarihi 8 Mart 2021
Kabul Tarihi 3 Nisan 2021
Yayımlandığı Sayı Yıl 2021

Kaynak Göster

APA Kasım, Ö. (2021). Speed Control of DC Motor under Reverse Torque Disturbance with Ant Colony Optimized PID Controller. Aksaray University Journal of Science and Engineering, 5(1), 8-19. https://doi.org/10.29002/asujse.892979

Cited By

Aksaray J. Sci. Eng. | e-ISSN: 2587-1277 | Period: Biannually | Founded: 2017 | Publisher: Aksaray University | https://asujse.aksaray.edu.tr