Research Article
BibTex RIS Cite

Genetic Algorithm based PID Tuning Software Design and Implementation for a DC Motor Control System

Year 2023, Volume: 10 Issue: 3, 286 - 300, 29.09.2023
https://doi.org/10.54287/gujsa.1342905

Abstract

This study presents the software and implementation for proportional-integral-derivative (PID) tuning of a DC motor control system using genetic algorithm (GA). The PID parameters for a specific control structure are optimized using GA in the proposed tuning procedure. Also, integral time absolute error (ITAE) is used as a fitness function to optimize the parameters. The robustness of the control system is compared with conventional mathematical method. Simulations are carried out in MATLAB/Simulink to compare the results of a DC motor control system. Simulation results show that in terms of overshoot, steady-state error, and settling time, GA-based PID tuning approach performed better than conventional method. Additionally, a sensitivity analysis is performed to evaluate how robust the proposed approach is to parameter variations. The analysis shows that compared to the conventional method, the GA-based PID tuning algorithm is more adaptable to variations in system parameters.

References

  • Alruim Alhasan, H., & Güneş, M. (2017). A New Adaptive Particle Swarm Optimization Based on Self-Tuning of PID Controller for DC Motor System. Çukurova University Journal of the Faculty of Engineering and Architecture, 32(3), 243-249.
  • Aranza, M. F., Kustija, J., Trisno, B., & Hakim, D. L. (2016). Tunning PID controller using particle swarm optimization algorithm on automatic voltage regulator system. IOP Conference Series: Materials Science and Engineering, 128, 012038. doi:10.1088/1757-899X/128/1/012038
  • Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2021). A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9(2), 818-827. doi:10.1007/s40435-020-00665-4
  • Fang, H., Zhou, J., Wang, Z., Qiu, Z., Sun, Y., Lin, Y., Chen, K., Zhou, X., & Pan, M. (2022). Hybrid method integrating machine learning and particle swarm optimization for smart chemical process operations. Frontiers of Chemical Science and Engineering, 16(2), 274-287. doi:10.1007/s11705-021-2043-0
  • de Figueiredo, R., Toso, B., & Schmith, J. (2023). Auto-Tuning PID Controller Based on Genetic Algorithm. In: M. Shamsuzzoha & G. L. Raja (Eds.), Disturbance Rejection Control. IntechOpen. doi:10.5772/INTECHOPEN.110143
  • Flores-Morán, E., Yánez-Pazmiño, W., Espín-Pazmiño, L., Carrera-Manosalvas, I., & Barzola-Monteses, J. (2020, October 13-16). Particle Swarm Optimization and Genetic Algorithm PID for DC motor position controllers. In: Proceedings of the 2020 IEEE ANDESCON, Quito, Ecuador. doi:10.1109/ANDESCON50619.2020.9272127
  • Galotto, L., Pinto, J. O. P., Bottura Filho, J. A., & Lambert-Torres, G. (2007, November 5-8). Recursive least square and genetic algorithm based tool for PID controllers tuning. In: Proceedings of the 2007 International Conference on Intelligent Systems Applications to Power Systems (ISAP), Kaohsiung, Taiwan. doi:10.1109/ISAP.2007.4441623
  • Ibrahim, O., Yahaya, N. Z. B., & Saad, N. (2016). PID Controller Response to Set-Point Change in DC-DC Converter Control. International Journal of Power Electronics and Drive Systems (IJPEDS), 7(2), 294-302. doi:10.11591/IJPEDS.V7.I2.PP294-302
  • Islam, Md. T., Karim, S. M. R., Sutradhar, A., & Miah, S. (2020). Fuzzy Logic and PID Controllers for DC Motor Using Genetic Algorithm. International Journal of Control Science and Engineering, 10(2), 37-41. doi:10.5923/J.CONTROL.20201002.03
  • Jayachitra, A., & Vinodha, R. (2014). Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor. Advances in Artificial Intelligence, 2014, 791230. doi:10.1155/2014/791230
  • Korkmaz, M., Aydoǧdu, Ö., & Doǧan, H. (2012, July 2-4). Design and performance comparison of variable parameter nonlinear PID controller and genetic algorithm based PID controller. In: Proceedings of the 2012 International Symposium on Innovations in Intelligent Systems and Applications (INISTA), Trabzon, Türkiye. doi:10.1109/INISTA.2012.6246935
  • Taşören, A. E. (2021). Design and Realization of Online Auto Tuning PID Controller Based on Cohen-Coon Method. European Journal of Science and Technology, 24 (Special Issue), 235-239. doi:10.31590/ejosat.897727
  • Malhotra, R., Singh, N., & Singh, Y. (2011). Genetic Algorithms: Concepts, Design for Optimization of Process Controllers. Computer and Information Science, 4(2), 39-54. doi:10.5539/CIS.V4N2P39
  • Martinez-Soltero, E. G., & Hernandez-Barragan, J. (2018). Robot Navigation Based on Differential Evolution. IFAC-PapersOnLine, 51(13), 350-354. doi:10.1016/J.IFACOL.2018.07.303
  • Meena, D. C., & Devanshu, A. (2017, January 19-20). Genetic algorithm tuned PID controller for process control. In: Proceedings of the 2017 International Conference on Inventive Systems and Control (ICISC), Coimbatore, India. doi:10.1109/ICISC.2017.8068639
  • Patel, V. V. (2020). Ziegler-Nichols Tuning Method: Understanding the PID Controller. Resonance, 25(10), 1385-1397. doi:10.1007/s12045-020-1058-z
  • Pereira, D. S., & Pinto, J. O. P. (2005, July 24-28). Genetic Algorithm based system identification and PID tuning for optimum adaptive control. In: Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Monterey, CA, USA, (pp. 801-806). doi:10.1109/AIM.2005.1511081
  • Rout, U. K., Sahu, R. K., & Panda, S. (2013). Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal, 4(3), 409-421. doi:10.1016/J.ASEJ.2012.10.010
  • Saad, M. S., Jamaluddin, H., & Darus, I. Z. M. (2012). Implementation of PID controller tuning using differential evolution and genetic algorithms. International Journal of Innovative Computing Information and Control, 8(11), 7761-7779.
  • Tiwari, S., Bhatt, A., Unni, A. C., Singh, J. G., & Ongsakul, W. (2018, October 24-26). Control of DC Motor Using Genetic Algorithm Based PID Controller. In: Proceedings of the 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), Phuket, Thailand. doi:10.23919/ICUE-GESD.2018.8635662
  • Wati, D. A. R., & Hidayat, R. (2013, November 25-27). Genetic algorithm-based PID parameters optimization for air heater temperature control. In: Proceedings of the 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems (ROBIONETICS), Jogjakarta, Indonesia, (pp. 30-34). doi:10.1109/ROBIONETICS.2013.6743573
Year 2023, Volume: 10 Issue: 3, 286 - 300, 29.09.2023
https://doi.org/10.54287/gujsa.1342905

Abstract

References

  • Alruim Alhasan, H., & Güneş, M. (2017). A New Adaptive Particle Swarm Optimization Based on Self-Tuning of PID Controller for DC Motor System. Çukurova University Journal of the Faculty of Engineering and Architecture, 32(3), 243-249.
  • Aranza, M. F., Kustija, J., Trisno, B., & Hakim, D. L. (2016). Tunning PID controller using particle swarm optimization algorithm on automatic voltage regulator system. IOP Conference Series: Materials Science and Engineering, 128, 012038. doi:10.1088/1757-899X/128/1/012038
  • Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2021). A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9(2), 818-827. doi:10.1007/s40435-020-00665-4
  • Fang, H., Zhou, J., Wang, Z., Qiu, Z., Sun, Y., Lin, Y., Chen, K., Zhou, X., & Pan, M. (2022). Hybrid method integrating machine learning and particle swarm optimization for smart chemical process operations. Frontiers of Chemical Science and Engineering, 16(2), 274-287. doi:10.1007/s11705-021-2043-0
  • de Figueiredo, R., Toso, B., & Schmith, J. (2023). Auto-Tuning PID Controller Based on Genetic Algorithm. In: M. Shamsuzzoha & G. L. Raja (Eds.), Disturbance Rejection Control. IntechOpen. doi:10.5772/INTECHOPEN.110143
  • Flores-Morán, E., Yánez-Pazmiño, W., Espín-Pazmiño, L., Carrera-Manosalvas, I., & Barzola-Monteses, J. (2020, October 13-16). Particle Swarm Optimization and Genetic Algorithm PID for DC motor position controllers. In: Proceedings of the 2020 IEEE ANDESCON, Quito, Ecuador. doi:10.1109/ANDESCON50619.2020.9272127
  • Galotto, L., Pinto, J. O. P., Bottura Filho, J. A., & Lambert-Torres, G. (2007, November 5-8). Recursive least square and genetic algorithm based tool for PID controllers tuning. In: Proceedings of the 2007 International Conference on Intelligent Systems Applications to Power Systems (ISAP), Kaohsiung, Taiwan. doi:10.1109/ISAP.2007.4441623
  • Ibrahim, O., Yahaya, N. Z. B., & Saad, N. (2016). PID Controller Response to Set-Point Change in DC-DC Converter Control. International Journal of Power Electronics and Drive Systems (IJPEDS), 7(2), 294-302. doi:10.11591/IJPEDS.V7.I2.PP294-302
  • Islam, Md. T., Karim, S. M. R., Sutradhar, A., & Miah, S. (2020). Fuzzy Logic and PID Controllers for DC Motor Using Genetic Algorithm. International Journal of Control Science and Engineering, 10(2), 37-41. doi:10.5923/J.CONTROL.20201002.03
  • Jayachitra, A., & Vinodha, R. (2014). Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor. Advances in Artificial Intelligence, 2014, 791230. doi:10.1155/2014/791230
  • Korkmaz, M., Aydoǧdu, Ö., & Doǧan, H. (2012, July 2-4). Design and performance comparison of variable parameter nonlinear PID controller and genetic algorithm based PID controller. In: Proceedings of the 2012 International Symposium on Innovations in Intelligent Systems and Applications (INISTA), Trabzon, Türkiye. doi:10.1109/INISTA.2012.6246935
  • Taşören, A. E. (2021). Design and Realization of Online Auto Tuning PID Controller Based on Cohen-Coon Method. European Journal of Science and Technology, 24 (Special Issue), 235-239. doi:10.31590/ejosat.897727
  • Malhotra, R., Singh, N., & Singh, Y. (2011). Genetic Algorithms: Concepts, Design for Optimization of Process Controllers. Computer and Information Science, 4(2), 39-54. doi:10.5539/CIS.V4N2P39
  • Martinez-Soltero, E. G., & Hernandez-Barragan, J. (2018). Robot Navigation Based on Differential Evolution. IFAC-PapersOnLine, 51(13), 350-354. doi:10.1016/J.IFACOL.2018.07.303
  • Meena, D. C., & Devanshu, A. (2017, January 19-20). Genetic algorithm tuned PID controller for process control. In: Proceedings of the 2017 International Conference on Inventive Systems and Control (ICISC), Coimbatore, India. doi:10.1109/ICISC.2017.8068639
  • Patel, V. V. (2020). Ziegler-Nichols Tuning Method: Understanding the PID Controller. Resonance, 25(10), 1385-1397. doi:10.1007/s12045-020-1058-z
  • Pereira, D. S., & Pinto, J. O. P. (2005, July 24-28). Genetic Algorithm based system identification and PID tuning for optimum adaptive control. In: Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Monterey, CA, USA, (pp. 801-806). doi:10.1109/AIM.2005.1511081
  • Rout, U. K., Sahu, R. K., & Panda, S. (2013). Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal, 4(3), 409-421. doi:10.1016/J.ASEJ.2012.10.010
  • Saad, M. S., Jamaluddin, H., & Darus, I. Z. M. (2012). Implementation of PID controller tuning using differential evolution and genetic algorithms. International Journal of Innovative Computing Information and Control, 8(11), 7761-7779.
  • Tiwari, S., Bhatt, A., Unni, A. C., Singh, J. G., & Ongsakul, W. (2018, October 24-26). Control of DC Motor Using Genetic Algorithm Based PID Controller. In: Proceedings of the 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), Phuket, Thailand. doi:10.23919/ICUE-GESD.2018.8635662
  • Wati, D. A. R., & Hidayat, R. (2013, November 25-27). Genetic algorithm-based PID parameters optimization for air heater temperature control. In: Proceedings of the 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems (ROBIONETICS), Jogjakarta, Indonesia, (pp. 30-34). doi:10.1109/ROBIONETICS.2013.6743573
There are 21 citations in total.

Details

Primary Language English
Subjects Evolutionary Computation, Electrical Machines and Drives
Journal Section Electrical & Electronics Engineering
Authors

Zafer Ortatepe 0000-0001-7771-1677

Early Pub Date September 21, 2023
Publication Date September 29, 2023
Submission Date August 14, 2023
Published in Issue Year 2023 Volume: 10 Issue: 3

Cite

APA Ortatepe, Z. (2023). Genetic Algorithm based PID Tuning Software Design and Implementation for a DC Motor Control System. Gazi University Journal of Science Part A: Engineering and Innovation, 10(3), 286-300. https://doi.org/10.54287/gujsa.1342905