Optimasi Pengendali PID untuk Alat Ukir Kaligrafi pada Mesin Computerized Numerical Control (CNC) berbasis Grey Wolf Optimization

Authors

  • Machrus Ali Universitas Darul Ulum
  • Muhammad Agil Haikal Universitas Darul Ulum
  • Fresy Nugroho UIN Maulana Malik Ibrahim Malang
  • Tri Mukti Lestari UIN Maulana Malik Ibrahim Malang
  • Dian Maharani UIN Maulana Malik Ibrahim Malang
  • Fuad Dwi Hanggara UIN Maulana Malik Ibrahim Malang
  • Fariz Rifqi Zul Fahmi UIN Maulana Malik Ibrahim Malang

DOI:

https://doi.org/10.30595/jrre.v8i1.30266

Keywords:

CNC, Grey Wolf Optimization, Kaligrafi, MATLAB/Simulink, PID

Abstract

Kualitas ukiran kaligrafi pada mesin CNC sangat dipengaruhi oleh akurasi pelacakan lintasan sumbu dan stabilitas gerak selama transisi kecepatan, tikungan tajam, dan variasi beban pemotongan. Pengontrol PID banyak digunakan dalam sistem servo CNC, namun penyetelan gain yang tidak tepat dapat meningkatkan kesalahan pelacakan, memperpanjang waktu penyelesaian, dan menyebabkan overshoot yang menurunkan kualitas permukaan. Studi ini mengusulkan penyetelan PID berbasis Grey Wolf Optimization (GWO) yang diimplementasikan dalam MATLAB/Simulink. Fungsi objektif didominasi oleh ITAE dengan penalti pada overshoot, waktu penyelesaian, dan kesalahan keadaan tunak. Selain uji pelacakan langkah dan sinusoidal, jalur alat kaligrafi yang berasal dari kode G (placeholder) disertakan untuk mewakili segmen dengan kelengkungan tinggi. Hasil penelitian menunjukkan bahwa PID yang disetel GWO mengurangi ITAE, meningkatkan waktu penyelesaian dibandingkan penyetelan konvensional, dan menurunkan kesalahan pelacakan RMS pada frekuensi rendah hingga menengah. Alur kerja yang diusulkan bersifat modular dan dapat digantikan oleh model plant yang teridentifikasi dari sumbu CNC nyata.

References

[1] B. Praveen, S. U. Abhishek, P. B. Shetty, J. Sudheer Reddy, and B. A. Praveena, “Industry 4.0 Researchers Computer Numerical Control Machine Tool to Manufacture Calligraphy Board,” in Lecture Notes in Electrical Engineering, 2022, pp. 197–206. doi: 10.1007/978-981-16-1342-5_15.

[2] P. B. Shetty, B. Praveen, U. S. Abhishek, and G. J. Naveen, “Mechatronics Computer Numerical Control Tool to Manufacture Calligraphy Board,” in 2023 IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2023, 2023. doi: 10.1109/ICICACS57338.2023.10100068.

[3] Y. Lu, Y. Fan, J. Zhao, S. Liu, and N. Chen, “Real-time arc length parameter-based integrated control strategy of contour error compensation for free-form curve CNC machining,” Int. J. Adv. Manuf. Technol., vol. 131, no. 3–4, pp. 1769–1794, 2024, doi: 10.1007/s00170-024-13030-y.

[4] B. Liu, H. Zhang, Y. Liu, and M. Lu, “A Feedrate Planning Method in CNC System Based on Servo Response Error Model,” Electronics, vol. 12, no. 14, p. 3150, Jul. 2023, doi: 10.3390/electronics12143150.

[5] M. Ali, “Optimasi Pemograman Sistem Pengendalian Mesin CNC Pengebor PCB Berdasar Metode Firefly Algorithm,” ALINIER J. Artif. Intell. Appl., vol. 3, no. 2, pp. 28–37, 2022, doi: 10.36040/alinier.v3i2.5840.

[6] E. Novrianto, M. Ali, and H. Nurohmah3, “Optimasi Perancangan Sistem Kontrol Mesin CNC Pengebor PCB berbasis Ant Colony Optimization,” Nucl. J., vol. 2, no. 2, pp. 82–94, 2023, doi: 10.32492/nucleus.v2i2.2202.

[7] X. Sun, B. Yang, Y. Gao, and Y. Yang, “Integrated design, fabrication, and experimental study of a parallel micro-nano positioning-vibration isolation stage,” Robot. Comput. Integr. Manuf., vol. 66, p. 101988, Dec. 2020, doi: 10.1016/j.rcim.2020.101988.

[8] T. Zhang, X. Li, H. Gai, Y. Zhu, and X. Cheng, “Integrated Controller Design and Application for CNC Machine Tool Servo Systems Based on Model Reference Adaptive Control and Adaptive Sliding Mode Control,” Sensors, vol. 23, no. 24, 2023, doi: 10.3390/s23249755.

[9] S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Adv. Eng. Softw., vol. 69, pp. 46–61, 2014, doi: 10.1016/j.advengsoft.2013.12.007.

[10] S. N. Makhadmeh et al., “Recent Advances in Grey Wolf Optimizer, its Versions and Applications: Review,” IEEE Access, vol. 12, pp. 22991–23028, 2024, doi: 10.1109/ACCESS.2023.3304889.

[11] M. Hasib Al Isbilly, Markhaban Siswanto, and Machrus Ali, “Optimasi PID Kontroller Pada Sistem Pengaturan Irigasi Menggunakan Metode Bat Algorithm,” J. JEETech, vol. 3, no. 2, pp. 78–83, 2022, doi: 10.48056/jeetech.v3i2.198.

[12] S. B. Joseph, E. G. Dada, A. Abidemi, D. O. Oyewola, and B. M. Khammas, “Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems,” 2022. doi: 10.1016/j.heliyon.2022.e09399.

[13] M. Ali and M. Ulum, “Perbandingan Optimasi Kontroler Putaran Motor Permanent Magnet Syschronous Machine,” J. FORTECH, vol. 1, no. 1, pp. 12–19, 2020, doi: 10.32492/fortech.v1i1.218.

[14] M. H. Nadimi-Shahraki, S. Taghian, and S. Mirjalili, “An improved grey wolf optimizer for solving engineering problems,” Expert Syst. Appl., vol. 166, 2021, doi: 10.1016/j.eswa.2020.113917.

[15] I. D. Fajuke and A. Raji, “Optimal tuning of PID controller for speed control of DC motor using equilibrium optimizer,” Indones. J. Electr. Eng. Comput. Sci., vol. 30, no. 1, pp. 89–101, 2023, doi: 10.11591/ijeecs.v30.i1.pp89-101.

Downloads

Published

2026-06-05

How to Cite

Ali, M., Agil Haikal, M., Nugroho, F., Mukti Lestari, T., Maharani, D., Dwi Hanggara, F., & Rifqi Zul Fahmi, F. (2026). Optimasi Pengendali PID untuk Alat Ukir Kaligrafi pada Mesin Computerized Numerical Control (CNC) berbasis Grey Wolf Optimization. Jurnal Riset Rekayasa Elektro, 8(1), 64–73. https://doi.org/10.30595/jrre.v8i1.30266