Research Article
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Year 2021, , 8 - 19, 30.06.2021

Ömer Kasım

https://doi.org/10.29002/asujse.892979
Cited By: 1

Abstract

References

  • [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

Year 2021, , 8 - 19, 30.06.2021

Ömer Kasım

https://doi.org/10.29002/asujse.892979
Cited By: 1

Abstract

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.

Keywords

DC Motor Speed Control PID Controller Ziegler Nichols method Ant Colony Optimization method

References

  • [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.
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Ömer Kasım 0000-0003-4021-5412

Publication Date June 30, 2021
Submission Date March 8, 2021
Acceptance Date April 3, 2021
Published in Issue Year 2021

Cite

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

Optimization of Servo Motor Control in Underwater Vehicles with PSO
Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi
https://doi.org/10.29137/umagd.1124999

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