Araştırma Makalesi
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Grey wolf optimizer-based PID controller design for an automobile cruise control system

Yıl 2026, Cilt: 15 Sayı: 1, 20 - 28, 24.03.2026
https://doi.org/10.18245/ijaet.1863402
https://izlik.org/JA66HH24NS

Öz

The cruise control systems are designed to maintain a desired speed of the vehicle and they can contribute to the comfort and fuel economy of the vehicle. Although PID controllers are popular for controlling the speed of the vehicle, their performance is highly sensitive to the choice of parameters. This paper presents the application of the Grey Wolf Optimizer algorithm for the optimization of PID controllers of a widely used cruise control system of an automobile by optimizing the Integral of Time-Weighted Squared Error (ITSE). The performance of the derived PID controller is analyzed in the time and frequency domains and the results are compared with the metaheuristic approaches available in the literature for the same plant model. The results show that the GWO optimized controller provides a stable closed-loop response and comparable performance in the time and frequency domains which confirms the applicability of GWO for the optimization of PID controllers of the cruise control system of an automobile.

Kaynakça

  • Osman, K., Rahmat, M.F., and Ahmad, M.A. Modelling and controller design for a cruise control system. 5th international colloquium on signal processing & its applications. IEEE. 254-258, 2009.
  • Frank, A.A., Liu, S., and Liang, S. "Longitudinal control concepts for automated automobiles and trucks operating on a cooperative highway", SAE transactions, 1308-1315, 1989.
  • Rajamani, R., Vehicle dynamics and control. Springer, 2006.
  • Musul, Z. and Cihan, O. "A novel system architecture of intelligent adaptive cruise control for safety aspects", International Journal of Automotive Engineering and Technologies, 13 (3), 103-113, 2024.
  • Asere, H., Lei, C., and Jia, R., Cruise Control Design Using Fuzzy Logic Controller, in 2015 IEEE International Conference on Systems, Man, and Cybernetics, p. 2210-2215, 2015
  • Onieva, E., Godoy, J., Villagrá, J., Milanés, V., and Pérez, J. "On-line learning of a fuzzy controller for a precise vehicle cruise control system", Expert Systems with Applications, 40(4), 1046-1053, 2013.
  • Simic, M. "Cascaded Fuzzy Logic for Adaptive Cruise Control", Mist International Journal of Science and Technology, 10, 33-40, 2022.
  • Naranjo, J.E., González, C., Reviejo, J., García, R., and De Pedro, T. "Adaptive fuzzy control for inter-vehicle gap keeping", IEEE Transactions on Intelligent Transportation Systems, 4(3), 132-142, 2003.
  • Wu, Z.W., Gao, Q.F., and Ren, H.L. "Variable Universe Fuzzy Control of Vehicle Cruise Control System Based on FSM Theory", Advanced Materials Research, 338, 141-151, 2011.
  • Muller, R. and Nocker, G., Intelligent cruise control with fuzzy logic. proceedings of the Intelligent Vehicles 92 Symposium. IEEE. 173-178, 1992.
  • Al-Saoudi, A.F., Al-Aubidy, K.M., and Al-Mahasneh, A.J., Comparison of PID, Fuzzy Logic, ANFIS and Model Predictive Controllers for Cruise Control System, in 2024 21st International Multi-Conference on Systems, Signals & Devices (SSD). 2024. p. 263-265, 2024.
  • Ogata, K., Modern control engineering, Prentice hall, 2010.
  • Li, S.E., Guo, Q., Xu, S., Duan, J., Li, S., Li, C., and Su, K. "Performance enhanced predictive control for adaptive cruise control system considering road elevation information", IEEE Transactions on Intelligent Vehicles, 2(3), 150-160, 2017.
  • Coşkun, S. and Köse, E. "Lean-burn air-fuel ratio control using genetic algorithm-based PI controller", International Journal of Automotive Engineering and Technologies, 10(3), 126-134, 2021.
  • Wang, H., Xu, S., and Hu, H. "PID controller for PMSM speed control based on improved quantum genetic algorithm optimization", IEEE Access, 11, 61091-61102, 2023.
  • Rout, M., Sain, D., Swain, S., and Mishra, S., PID controller design for cruise control system using genetic algorithm. 2016 international conference on electrical, electronics, and optimization techniques (ICEEOT). IEEE. 4170-4174, 2016.
  • Chirantan, S., Prusty, C., and Pati, B.B. "An investigation into the stability of a car cruise control system using Ziegler Nichols and a Genetic Algorithm-tuned PID controller", Engineering Research Express, 8(1), 2026.
  • Mahmood, A., Al-bayati, K.Y.A., and Szabolcsi, R. "Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System", World Electric Vehicle Journal, 15(8), 2024.
  • Salem, N., Hassan, R., and Muthanna, L., Enhancing Cruise Performance Through PID Controller Tuned with Particle Swarm Optimization Technique, in 2023 6th International Conference on Intelligent Robotics and Control Engineering (IRCE), p. 23-28, 2023.
  • Chaturvedi, S. and Kumar, N. "Design and Implementation of an Optimized PID Controller for the Adaptive Cruise Control System", IETE Journal of Research, 69(10), 7084-7091, 2021.
  • Abdulnabi, A. "PID controller design for cruise control system using particle swarm optimization", Iraqi Journal for computers and Informatics, 43(2), 30-35, 2017.
  • Pradhan, R., Majhi, S.K., Pradhan, J.K., and Pati, B.B. "Antlion optimizer tuned PID controller based on Bode ideal transfer function for automobile cruise control system", Journal of Industrial Information Integration, 9, 45-52, 2018.
  • İzci, D., Ekinci, S., Kayri, M., and Eker, E. "A Novel Enhanced Metaheuristic Algorithm for Automobile Cruise Control System", Electrica, 21(3), 283-297, 2021.
  • Ekinci, S., Izci, D., Abualigah, L., and Zitar, R.A. "A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System", Journal of Bionic Engineering, 20(4), 1828-1851, 2023.
  • Hlangnamthip, S., Thammarat, C., Sinsukudomchai, C., and Puangdownreong, D., Optimal Tuning of PIDA Controller for Vehicle Cruise Control System by Modified Bat Algorithm, in 2024 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), p. 108-111, 2024.
  • Saravanan, G., Pazhanimuthu, C., Sathish Kumar, D., Lalitha, B., Senthilkumar, M., and Kannan, E. 2024. Red Panda Optimization Algorithm-Based PID Controller Design for Automobile Cruise Control System. International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC). IEEE. 33-37, 2024.
  • Jing, Z. "Application of genetic fuzzy immune PID algorithm in cruise control for commercial vehicles", AIP Advances, 10(9), 2020.
  • Mirjalili, S., Mirjalili, S.M., and Lewis, A. "Grey Wolf Optimizer", Advances in Engineering Software, 69, 46-61, 2014.

Otomobil Hız Sabitleme Sistemi için Gri Kurt Optimizasyon Algoritması Tabanlı PID Kontrolcü Tasarımı

Yıl 2026, Cilt: 15 Sayı: 1, 20 - 28, 24.03.2026
https://doi.org/10.18245/ijaet.1863402
https://izlik.org/JA66HH24NS

Öz

Hız sabitleme sistemleri, modern otomobillerde yol güvenliğini, sürücü konforunu ve yakıt ekonomisini artırmak amacıyla tasarlanmıştır. PID kontrolcüler, araç hız kontrolü için endüstride yaygın olarak kullanılmakla birlikte, parametrelerinin dikkatli biçimde ayarlanmasını gerektirir. Bu çalışmada, doğadan esinlenilmiş bir meta-sezgisel algoritma olan Gri Kurt Optimizasyonu (GWO) kullanılarak optimum kontrol kazançları elde edilmiştir. Hata değerlerini zaman ilerledikçe daha fazla ağırlıklandırarak hızlı bir yanıt elde etmek ve hataları zamanla azaltmak amacıyla amaç fonksiyonu olarak Zaman Ağırlıklı Kare Hata İntegrali (ITSE) seçilmiştir. Optimum parametreleri belirlenen kontrolcünün performansı, aynı sistem modelini kullanan ve literatürde yer alan güncel optimizasyon algoritmalarıyla karşılaştırılmıştır. Geçici rejim yanıtı ölçütleri ve frekans yanıtı özellikleri birlikte değerlendirildiğinde, GWO’nun araç hız sabitleme sistemlerinde kontrol optimizasyonu için uygulanabilir bir alternatif olduğu görülmüştür. Önerilen yöntem, hız regülasyonu açısından tatmin edici bir performans sağlamaktadır. Araştırmaya ait sonuçlar ve performans indisleri tablolar ve şekiller halinde sunulmuştur.

Kaynakça

  • Osman, K., Rahmat, M.F., and Ahmad, M.A. Modelling and controller design for a cruise control system. 5th international colloquium on signal processing & its applications. IEEE. 254-258, 2009.
  • Frank, A.A., Liu, S., and Liang, S. "Longitudinal control concepts for automated automobiles and trucks operating on a cooperative highway", SAE transactions, 1308-1315, 1989.
  • Rajamani, R., Vehicle dynamics and control. Springer, 2006.
  • Musul, Z. and Cihan, O. "A novel system architecture of intelligent adaptive cruise control for safety aspects", International Journal of Automotive Engineering and Technologies, 13 (3), 103-113, 2024.
  • Asere, H., Lei, C., and Jia, R., Cruise Control Design Using Fuzzy Logic Controller, in 2015 IEEE International Conference on Systems, Man, and Cybernetics, p. 2210-2215, 2015
  • Onieva, E., Godoy, J., Villagrá, J., Milanés, V., and Pérez, J. "On-line learning of a fuzzy controller for a precise vehicle cruise control system", Expert Systems with Applications, 40(4), 1046-1053, 2013.
  • Simic, M. "Cascaded Fuzzy Logic for Adaptive Cruise Control", Mist International Journal of Science and Technology, 10, 33-40, 2022.
  • Naranjo, J.E., González, C., Reviejo, J., García, R., and De Pedro, T. "Adaptive fuzzy control for inter-vehicle gap keeping", IEEE Transactions on Intelligent Transportation Systems, 4(3), 132-142, 2003.
  • Wu, Z.W., Gao, Q.F., and Ren, H.L. "Variable Universe Fuzzy Control of Vehicle Cruise Control System Based on FSM Theory", Advanced Materials Research, 338, 141-151, 2011.
  • Muller, R. and Nocker, G., Intelligent cruise control with fuzzy logic. proceedings of the Intelligent Vehicles 92 Symposium. IEEE. 173-178, 1992.
  • Al-Saoudi, A.F., Al-Aubidy, K.M., and Al-Mahasneh, A.J., Comparison of PID, Fuzzy Logic, ANFIS and Model Predictive Controllers for Cruise Control System, in 2024 21st International Multi-Conference on Systems, Signals & Devices (SSD). 2024. p. 263-265, 2024.
  • Ogata, K., Modern control engineering, Prentice hall, 2010.
  • Li, S.E., Guo, Q., Xu, S., Duan, J., Li, S., Li, C., and Su, K. "Performance enhanced predictive control for adaptive cruise control system considering road elevation information", IEEE Transactions on Intelligent Vehicles, 2(3), 150-160, 2017.
  • Coşkun, S. and Köse, E. "Lean-burn air-fuel ratio control using genetic algorithm-based PI controller", International Journal of Automotive Engineering and Technologies, 10(3), 126-134, 2021.
  • Wang, H., Xu, S., and Hu, H. "PID controller for PMSM speed control based on improved quantum genetic algorithm optimization", IEEE Access, 11, 61091-61102, 2023.
  • Rout, M., Sain, D., Swain, S., and Mishra, S., PID controller design for cruise control system using genetic algorithm. 2016 international conference on electrical, electronics, and optimization techniques (ICEEOT). IEEE. 4170-4174, 2016.
  • Chirantan, S., Prusty, C., and Pati, B.B. "An investigation into the stability of a car cruise control system using Ziegler Nichols and a Genetic Algorithm-tuned PID controller", Engineering Research Express, 8(1), 2026.
  • Mahmood, A., Al-bayati, K.Y.A., and Szabolcsi, R. "Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System", World Electric Vehicle Journal, 15(8), 2024.
  • Salem, N., Hassan, R., and Muthanna, L., Enhancing Cruise Performance Through PID Controller Tuned with Particle Swarm Optimization Technique, in 2023 6th International Conference on Intelligent Robotics and Control Engineering (IRCE), p. 23-28, 2023.
  • Chaturvedi, S. and Kumar, N. "Design and Implementation of an Optimized PID Controller for the Adaptive Cruise Control System", IETE Journal of Research, 69(10), 7084-7091, 2021.
  • Abdulnabi, A. "PID controller design for cruise control system using particle swarm optimization", Iraqi Journal for computers and Informatics, 43(2), 30-35, 2017.
  • Pradhan, R., Majhi, S.K., Pradhan, J.K., and Pati, B.B. "Antlion optimizer tuned PID controller based on Bode ideal transfer function for automobile cruise control system", Journal of Industrial Information Integration, 9, 45-52, 2018.
  • İzci, D., Ekinci, S., Kayri, M., and Eker, E. "A Novel Enhanced Metaheuristic Algorithm for Automobile Cruise Control System", Electrica, 21(3), 283-297, 2021.
  • Ekinci, S., Izci, D., Abualigah, L., and Zitar, R.A. "A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System", Journal of Bionic Engineering, 20(4), 1828-1851, 2023.
  • Hlangnamthip, S., Thammarat, C., Sinsukudomchai, C., and Puangdownreong, D., Optimal Tuning of PIDA Controller for Vehicle Cruise Control System by Modified Bat Algorithm, in 2024 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), p. 108-111, 2024.
  • Saravanan, G., Pazhanimuthu, C., Sathish Kumar, D., Lalitha, B., Senthilkumar, M., and Kannan, E. 2024. Red Panda Optimization Algorithm-Based PID Controller Design for Automobile Cruise Control System. International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC). IEEE. 33-37, 2024.
  • Jing, Z. "Application of genetic fuzzy immune PID algorithm in cruise control for commercial vehicles", AIP Advances, 10(9), 2020.
  • Mirjalili, S., Mirjalili, S.M., and Lewis, A. "Grey Wolf Optimizer", Advances in Engineering Software, 69, 46-61, 2014.
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Otomotiv Mühendisliği (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Abdullah Çakan 0000-0003-3923-4069

Gönderilme Tarihi 14 Ocak 2026
Kabul Tarihi 16 Şubat 2026
Yayımlanma Tarihi 24 Mart 2026
DOI https://doi.org/10.18245/ijaet.1863402
IZ https://izlik.org/JA66HH24NS
Yayımlandığı Sayı Yıl 2026 Cilt: 15 Sayı: 1

Kaynak Göster

APA Çakan, A. (2026). Grey wolf optimizer-based PID controller design for an automobile cruise control system. International Journal of Automotive Engineering and Technologies, 15(1), 20-28. https://doi.org/10.18245/ijaet.1863402
AMA 1.Çakan A. Grey wolf optimizer-based PID controller design for an automobile cruise control system. International Journal of Automotive Engineering and Technologies. 2026;15(1):20-28. doi:10.18245/ijaet.1863402
Chicago Çakan, Abdullah. 2026. “Grey wolf optimizer-based PID controller design for an automobile cruise control system”. International Journal of Automotive Engineering and Technologies 15 (1): 20-28. https://doi.org/10.18245/ijaet.1863402.
EndNote Çakan A (01 Mart 2026) Grey wolf optimizer-based PID controller design for an automobile cruise control system. International Journal of Automotive Engineering and Technologies 15 1 20–28.
IEEE [1]A. Çakan, “Grey wolf optimizer-based PID controller design for an automobile cruise control system”, International Journal of Automotive Engineering and Technologies, c. 15, sy 1, ss. 20–28, Mar. 2026, doi: 10.18245/ijaet.1863402.
ISNAD Çakan, Abdullah. “Grey wolf optimizer-based PID controller design for an automobile cruise control system”. International Journal of Automotive Engineering and Technologies 15/1 (01 Mart 2026): 20-28. https://doi.org/10.18245/ijaet.1863402.
JAMA 1.Çakan A. Grey wolf optimizer-based PID controller design for an automobile cruise control system. International Journal of Automotive Engineering and Technologies. 2026;15:20–28.
MLA Çakan, Abdullah. “Grey wolf optimizer-based PID controller design for an automobile cruise control system”. International Journal of Automotive Engineering and Technologies, c. 15, sy 1, Mart 2026, ss. 20-28, doi:10.18245/ijaet.1863402.
Vancouver 1.Abdullah Çakan. Grey wolf optimizer-based PID controller design for an automobile cruise control system. International Journal of Automotive Engineering and Technologies. 01 Mart 2026;15(1):20-8. doi:10.18245/ijaet.1863402