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Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control

Yıl 2025, ERKEN GÖRÜNÜM, 1 - 1

Kadir Yasin Sunca , Ali Fuat Boz

https://doi.org/10.2339/politeknik.1687239

Öz

The Artificial Hummingbird Algorithm (AHA), a meta-heuristic algorithm that mimics hummingbird feeding behaviours and was inspired by nature, was published in 2021 by Liying Wang. This approach uses axial, diagonal, and omnidirectional flight capabilities to carry out migration and foraging processes in a directed manner. The AHA was used in this study to analysed the direct current (DC) motor speed control problem based on proportional-integral-derivative (PID) controllers. The integral of the time-weighted absolute error (ITAE) was employed as an error-based objective function for parameter optimization once the ideal PID parameters (kp, ki, and kd) were identified in the controller design. The AHA was contrasted with other algorithms from the literature at various DC motor operating points in order to increase diversity. The results showed that the AHA that was suggested performed successfully and effectively for the DC motor speed control problem.

Anahtar Kelimeler

AHA PID Controllers DC Motor Control Parameters.

Etik Beyan

The authors of this article declare that ethical committee approval and/or legal/special permission were not required for the materials and methods used in their study.

Destekleyen Kurum

No support was received from any institution or organization.

Kaynakça

  • [1] A. F. Güven, “Exploring Solar Energy Systems: A Comparative Study of Optimization Algorithms, MPPTs, and Controllers,” IET Control Theory& Applications (18)7:887–920., (2024).
  • [2] Ekinci S. and Hekimoğlu B., “Improved kidney-inspired algorithm approach for tuning of PID Controller in AVR system”. IEEE Access 7: 39935–39947. (2019).
  • [3] Xia, C. L., “Permanent magnet brushless DC motor drives and controls.” John Wiley & Sons. (2012).
  • [4] Gamazo-Real, J. C., Vázquez-Sánchez, E., & Gómez-Gil, J. “Position and speed control of brushless DC motors using sensorless techniques and application trends”. Sensors, 10(7), 6901-6947. (2010).
  • [5] Zhao, X., Sun, Y., Li, Y., Jia, N., & Xu, J. “Applications of machine learning in real-time control systems: a review.”Measurement Science and Technology., (2024).
  • [6] Saini R., Parmar G., Gupta R. SFS based Fractional Order “PID Controller (FOPID) for Speed Control of DC Motor.” International Journal, 9 (4)., (2020).
  • [7] Wang M.S., Chen S.C., Shih C.H., "Speed control of brushless DC motor by adaptive network-based fuzzy inference. Microsystem Technologies", 24 (1): 33-39. (2018).
  • [8] Varshney A., Gupta D., Dwivedi B. “Speed response of brushless DC motor using fuzzy PID controller under varying load condition.” Journal of Electrical Systems and Information Technology, 4 (2): 310-321. (2017).
  • [9] Dursun E.H., Durdu A. “Speed control of a DC motor with variable load using sliding mode control.” International Journal of Computer and Electrical Engineering, 8 (3): 219-226. (2016).
  • [10] Jacquot RG., “Modern digital control systems”, Routledge. (2019).
  • [11] Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Le´vy flight distribution and Nelder–Mead algorithm
  • [12] Güven, A. F., Mengi, O. Ö., Elseify, M. A., & Kamel, S. “Comprehensive optimization of PID controller parameters for DC motor speed management using a modified jellyfish search algorithm.” Optimal Control Applications and Methods, 46(1), 320-342., (2025).
  • [13] Alkrwy, A., Hussein, A. A., Atyia, T. H., & Khamees, M. “Adaptive tuning of PID controller using crow Search algorithm for DC motor.” In IOP Conference Series: Materials Science and Engineering (Vol. 1076, No. 1, p. 012001). IOP Publishing., (2021).
  • [14] Idir, A., Khettab, K., & Bensafia, Y., “Design of an optimally tuned fractionalized PID controller for dc motor speed control via a henry gas solubility optimization algorithm.” Int. J. Intell. Eng. Syst, 15(2), 59. (2022).
  • [15] Aribowo, W., Supari, S., & Suprianto, B. “Optimization of PID parameters for controlling DC motor based on the aquila optimizer algorithm.” International Journal of Power Electronics and Drive Systems, 13(1), 216., (2022).
  • [16] Acharya, B. B., Dhakal, S., Bhattarai, A., & Bhattarai, N. “PID speed control of DC motor using meta-heuristic algorithms.” International Journal of Power Electronics and Drive Systems, 12(2), 822., (2021).
  • [17] Ekinci, S., Hekimoğlu, B., & Izci, D., “Opposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motor.” Engineering Science and Technology, an International Journal, 24(2), 331-342. (2021).
  • [18] Jabari, M., Ekinci, S., Izci, D., Bajaj, M., & Zaitsev, I. “Efficient DC motor speed control using a novel multi-stage FOPD (1+ PI) controller optimized by the Pelican optimization algorithm.” Scientific Reports, 14(1), 22442. (2024).
  • [19] Musa, M. A., & Jayachitra, T., “Ant Lion Optimization Based PID Controller in DC Motor Speed Control.” In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) (1):1-6. IEEE., (2024).
  • [20] Agarwal, J., Parmar, G., Gupta, R., & Sikander, A. “Analysis of grey wolf optimizer based fractional order PID controller in speed control of DC motor.” Microsystem Technologies, 24, 4997-5006. (2018).
  • [21] Khanam I., Parmar G. “Application of SFS algorithm in control of DC motor and comparative analysis.” In 2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON), October, 256-261., (2017).
  • [22] Çelik, E., & Gör, H., “Enhanced speed control of a DC servo system using PI+ DF controller tuned by stochastic fractal search technique. Journal of the Franklin Institute, 356(3), 1333-1359., (2019).
  • [23] Celik, E., & Öztürk, N., “First application of symbiotic organisms search algorithm to off-line optimization of PI parameters for DSP-based DC motor drives.” Neural Computing and Applications, 30, 1689-1699. (2018).
  • [24] Çelik, E., & Öztürk, N., “Doğru akım motor sürücüleri için PI parametrelerinin simbiyotik organizmalar arama algoritması ile optimal ayarı.” Bilişim Teknolojileri Dergisi, 10(3), 311-318., (2017).
  • [25] Çelik, E., Dalcali, A., Öztürk, N., & Canbaz, R., “An adaptive PI controller schema based on fuzzy logic controller for speed control of permanent magnet synchronous motors.” In 4th international conference on power engineering, energy and electrical drives (pp. 715-720). IEEE. (2013).
  • [26] Çelik, E., Bal, G., Öztürk, N., Bekiroglu, E., Houssein, E. H., Ocak, C., & Sharma, G., “Improving speed control characteristics of PMDC motor drives using nonlinear PI control.” Neural Computing and Applications, 36(16), 9113-9124., (2024).
  • [27] Zhao, W., Wang, L., & Mirjalili, S., “Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications.” Computer Methods in Applied Mechanics and Engineering, 388, 114194., (2022).
  • [28] Başlık Ş., Sesli E. and Akyazı Ö., “Effect of derivative filter usage on a pıd controller optimized via pathfinder algorithm: an example of a DC-MSCS”, Journal of Polytechnic, 27(1): 185-196, (2024).
  • [29] Hekimoğlu, B., “Böbrek-ilhamlı algoritma ile ayarlanan PID kontrolör kullanarak DC motor hız kontrolü.” Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 8(2), 652-663. (2019).
  • [30] Şahin, A. K., Akyazı, Ö., Sahın, E., & Çakır, O., “DC Motorun hız kontrolü için meta-sezgisel algoritma tabanlı PID denetleyici tasarımı”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 10(2), 533-549. (2021).
  • [31] Çavdar B., Şahin E. ve Nuroğlu F.M., “Doğru akım motoru hız kontrolü için SAA tabanlı kesir dereceli PI-PD eklemeli denetleyici tasarımı”, Journal of Polytechnic, 27(1): 283-296, (2024).
  • [32] S. Ekinci, D. Izci, and B. Hekimoglu, “PID Speed Control of DC Motor Using Harris Hawks Optimization Algorithm,” in 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), IEEE, Jun. 1–6. (2020).
  • [33] B. Hekimoglu, “Optimal Tuning of Fractional Order PID Controller for DC Motor Speed Control via Chaotic Atom Search Optimization Algorithm,” IEEE Access, (7):38100–38114, (2019).
  • [34] J. Agarwal, G. Parmar, and R. Gupta, “Application of sine cosine algorithm in optimal control of DC motor and robustness analysis,” Wulfenia J, 24(11):77–95, (2017).
  • [35] Khalilpour R., Razmjooy A., Hosseini H., Moallem P. “Optimal control of DC motor using invasive weed optimization.”, (2011).
  • [36] Sonugür G., “DA motor kontrolünde veri güdümlü ve model tabanlı yöntemlerin ani yük değişimlerine karşı tepkilerinin analizi”, Journal of Polytechnic, 27(5): 1721-1732, (2024).

DC Motor Hız Kontrolü için Yapay Sinek Kuşu Algoritması Tabanlı PID Denetleyici

Yıl 2025, ERKEN GÖRÜNÜM, 1 - 1

Kadir Yasin Sunca , Ali Fuat Boz

https://doi.org/10.2339/politeknik.1687239

Öz

Sinek kuşlarının beslenme davranışlarını taklit eden ve doğadan ilham alan meta-sezgisel bir algoritma olan Yapay Sinek Kuşu Algoritması (AHA), 2021 yılında Liying Wang tarafından yayınlanmıştır. Bu yaklaşım, göç ve yiyecek arama süreçlerini yönlendirilmiş bir şekilde yürütmek için eksenel, çapraz ve çok yönlü uçuş yeteneklerini kullanmaktadır. AHA, bu çalışmada oransal-integral-türev (PID) kontrolörlerine dayalı doğru akım (DC) motor hız kontrol problemini analiz etmek için kullanılmıştır. Zaman ağırlıklı mutlak hatanın (ITAE) integrali, kontrolör tasarımında ideal PID parametreleri (kp, ki ve kd) belirlendikten sonra parametre optimizasyonu için hata tabanlı bir amaç fonksiyonu olarak kullanılmıştır. AHA, çeşitliliği artırmak amacıyla çeşitli DC motor çalışma noktalarında literatürdeki diğer algoritmalarla karşılaştırılmıştır. Sonuçlar, önerilen AHA'nın DC motor hız kontrol problemi için başarılı ve etkili bir performans sergilediğini göstermiştir.

Anahtar Kelimeler

AHA PID Denetleyiciler DC Motor Kontrol Parametreleri.

Kaynakça

  • [1] A. F. Güven, “Exploring Solar Energy Systems: A Comparative Study of Optimization Algorithms, MPPTs, and Controllers,” IET Control Theory& Applications (18)7:887–920., (2024).
  • [2] Ekinci S. and Hekimoğlu B., “Improved kidney-inspired algorithm approach for tuning of PID Controller in AVR system”. IEEE Access 7: 39935–39947. (2019).
  • [3] Xia, C. L., “Permanent magnet brushless DC motor drives and controls.” John Wiley & Sons. (2012).
  • [4] Gamazo-Real, J. C., Vázquez-Sánchez, E., & Gómez-Gil, J. “Position and speed control of brushless DC motors using sensorless techniques and application trends”. Sensors, 10(7), 6901-6947. (2010).
  • [5] Zhao, X., Sun, Y., Li, Y., Jia, N., & Xu, J. “Applications of machine learning in real-time control systems: a review.”Measurement Science and Technology., (2024).
  • [6] Saini R., Parmar G., Gupta R. SFS based Fractional Order “PID Controller (FOPID) for Speed Control of DC Motor.” International Journal, 9 (4)., (2020).
  • [7] Wang M.S., Chen S.C., Shih C.H., "Speed control of brushless DC motor by adaptive network-based fuzzy inference. Microsystem Technologies", 24 (1): 33-39. (2018).
  • [8] Varshney A., Gupta D., Dwivedi B. “Speed response of brushless DC motor using fuzzy PID controller under varying load condition.” Journal of Electrical Systems and Information Technology, 4 (2): 310-321. (2017).
  • [9] Dursun E.H., Durdu A. “Speed control of a DC motor with variable load using sliding mode control.” International Journal of Computer and Electrical Engineering, 8 (3): 219-226. (2016).
  • [10] Jacquot RG., “Modern digital control systems”, Routledge. (2019).
  • [11] Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Le´vy flight distribution and Nelder–Mead algorithm
  • [12] Güven, A. F., Mengi, O. Ö., Elseify, M. A., & Kamel, S. “Comprehensive optimization of PID controller parameters for DC motor speed management using a modified jellyfish search algorithm.” Optimal Control Applications and Methods, 46(1), 320-342., (2025).
  • [13] Alkrwy, A., Hussein, A. A., Atyia, T. H., & Khamees, M. “Adaptive tuning of PID controller using crow Search algorithm for DC motor.” In IOP Conference Series: Materials Science and Engineering (Vol. 1076, No. 1, p. 012001). IOP Publishing., (2021).
  • [14] Idir, A., Khettab, K., & Bensafia, Y., “Design of an optimally tuned fractionalized PID controller for dc motor speed control via a henry gas solubility optimization algorithm.” Int. J. Intell. Eng. Syst, 15(2), 59. (2022).
  • [15] Aribowo, W., Supari, S., & Suprianto, B. “Optimization of PID parameters for controlling DC motor based on the aquila optimizer algorithm.” International Journal of Power Electronics and Drive Systems, 13(1), 216., (2022).
  • [16] Acharya, B. B., Dhakal, S., Bhattarai, A., & Bhattarai, N. “PID speed control of DC motor using meta-heuristic algorithms.” International Journal of Power Electronics and Drive Systems, 12(2), 822., (2021).
  • [17] Ekinci, S., Hekimoğlu, B., & Izci, D., “Opposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motor.” Engineering Science and Technology, an International Journal, 24(2), 331-342. (2021).
  • [18] Jabari, M., Ekinci, S., Izci, D., Bajaj, M., & Zaitsev, I. “Efficient DC motor speed control using a novel multi-stage FOPD (1+ PI) controller optimized by the Pelican optimization algorithm.” Scientific Reports, 14(1), 22442. (2024).
  • [19] Musa, M. A., & Jayachitra, T., “Ant Lion Optimization Based PID Controller in DC Motor Speed Control.” In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) (1):1-6. IEEE., (2024).
  • [20] Agarwal, J., Parmar, G., Gupta, R., & Sikander, A. “Analysis of grey wolf optimizer based fractional order PID controller in speed control of DC motor.” Microsystem Technologies, 24, 4997-5006. (2018).
  • [21] Khanam I., Parmar G. “Application of SFS algorithm in control of DC motor and comparative analysis.” In 2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON), October, 256-261., (2017).
  • [22] Çelik, E., & Gör, H., “Enhanced speed control of a DC servo system using PI+ DF controller tuned by stochastic fractal search technique. Journal of the Franklin Institute, 356(3), 1333-1359., (2019).
  • [23] Celik, E., & Öztürk, N., “First application of symbiotic organisms search algorithm to off-line optimization of PI parameters for DSP-based DC motor drives.” Neural Computing and Applications, 30, 1689-1699. (2018).
  • [24] Çelik, E., & Öztürk, N., “Doğru akım motor sürücüleri için PI parametrelerinin simbiyotik organizmalar arama algoritması ile optimal ayarı.” Bilişim Teknolojileri Dergisi, 10(3), 311-318., (2017).
  • [25] Çelik, E., Dalcali, A., Öztürk, N., & Canbaz, R., “An adaptive PI controller schema based on fuzzy logic controller for speed control of permanent magnet synchronous motors.” In 4th international conference on power engineering, energy and electrical drives (pp. 715-720). IEEE. (2013).
  • [26] Çelik, E., Bal, G., Öztürk, N., Bekiroglu, E., Houssein, E. H., Ocak, C., & Sharma, G., “Improving speed control characteristics of PMDC motor drives using nonlinear PI control.” Neural Computing and Applications, 36(16), 9113-9124., (2024).
  • [27] Zhao, W., Wang, L., & Mirjalili, S., “Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications.” Computer Methods in Applied Mechanics and Engineering, 388, 114194., (2022).
  • [28] Başlık Ş., Sesli E. and Akyazı Ö., “Effect of derivative filter usage on a pıd controller optimized via pathfinder algorithm: an example of a DC-MSCS”, Journal of Polytechnic, 27(1): 185-196, (2024).
  • [29] Hekimoğlu, B., “Böbrek-ilhamlı algoritma ile ayarlanan PID kontrolör kullanarak DC motor hız kontrolü.” Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 8(2), 652-663. (2019).
  • [30] Şahin, A. K., Akyazı, Ö., Sahın, E., & Çakır, O., “DC Motorun hız kontrolü için meta-sezgisel algoritma tabanlı PID denetleyici tasarımı”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 10(2), 533-549. (2021).
  • [31] Çavdar B., Şahin E. ve Nuroğlu F.M., “Doğru akım motoru hız kontrolü için SAA tabanlı kesir dereceli PI-PD eklemeli denetleyici tasarımı”, Journal of Polytechnic, 27(1): 283-296, (2024).
  • [32] S. Ekinci, D. Izci, and B. Hekimoglu, “PID Speed Control of DC Motor Using Harris Hawks Optimization Algorithm,” in 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), IEEE, Jun. 1–6. (2020).
  • [33] B. Hekimoglu, “Optimal Tuning of Fractional Order PID Controller for DC Motor Speed Control via Chaotic Atom Search Optimization Algorithm,” IEEE Access, (7):38100–38114, (2019).
  • [34] J. Agarwal, G. Parmar, and R. Gupta, “Application of sine cosine algorithm in optimal control of DC motor and robustness analysis,” Wulfenia J, 24(11):77–95, (2017).
  • [35] Khalilpour R., Razmjooy A., Hosseini H., Moallem P. “Optimal control of DC motor using invasive weed optimization.”, (2011).
  • [36] Sonugür G., “DA motor kontrolünde veri güdümlü ve model tabanlı yöntemlerin ani yük değişimlerine karşı tepkilerinin analizi”, Journal of Polytechnic, 27(5): 1721-1732, (2024).
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Memnuniyet ve Optimizasyon, Elektrik Makineleri ve Sürücüler, Kontrol Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Kadir Yasin Sunca 0009-0006-5024-7820

Ali Fuat Boz 0000-0001-6575-7678

Erken Görünüm Tarihi 9 Haziran 2025
Yayımlanma Tarihi
Gönderilme Tarihi 30 Nisan 2025
Kabul Tarihi 3 Haziran 2025
Yayımlandığı Sayı Yıl 2025 ERKEN GÖRÜNÜM

Kaynak Göster

APA Sunca, K. Y., & Boz, A. F. (2025). Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control. Politeknik Dergisi1-1. https://doi.org/10.2339/politeknik.1687239
AMA Sunca KY, Boz AF. Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control. Politeknik Dergisi. Published online 01 Haziran 2025:1-1. doi:10.2339/politeknik.1687239
Chicago Sunca, Kadir Yasin, ve Ali Fuat Boz. “Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control”. Politeknik Dergisi, Haziran (Haziran 2025), 1-1. https://doi.org/10.2339/politeknik.1687239.
EndNote Sunca KY, Boz AF (01 Haziran 2025) Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control. Politeknik Dergisi 1–1.
IEEE K. Y. Sunca ve A. F. Boz, “Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control”, Politeknik Dergisi, ss. 1–1, Haziran 2025, doi: 10.2339/politeknik.1687239.
ISNAD Sunca, Kadir Yasin - Boz, Ali Fuat. “Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control”. Politeknik Dergisi. Haziran 2025. 1-1. https://doi.org/10.2339/politeknik.1687239.
JAMA Sunca KY, Boz AF. Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control. Politeknik Dergisi. 2025;:1–1.
MLA Sunca, Kadir Yasin ve Ali Fuat Boz. “Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control”. Politeknik Dergisi, 2025, ss. 1-1, doi:10.2339/politeknik.1687239.
Vancouver Sunca KY, Boz AF. Artificial Hummingbird Algorithm- Based PID Controller for DC Motor Speed Control. Politeknik Dergisi. 2025:1-.
 
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