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Genetik Algoritma ile Optimize Edilmiş Yenilikçi bir Gecikmeli Rezonatör ile Çeyrek Taşıt Modelinin Kontrolü

Year 2024, , 189 - 196, 27.02.2024
https://doi.org/10.35414/akufemubid.1330683

Abstract

Bu çalışma, çeyrek araç modelini kullanmış ve aktif süspansiyon sistemini düzenlemek için bir gecikmeli rezonatör kontrol yaklaşımı uygulamıştır. Geleneksel gecikmeli rezonatörün aksine, bu çalışmada kuvvet sinyali konum, hız ve ivme gecikmeli rezonatörün uygulanmasıyla üretilir. gecikmeli rezonatör denetleyicisinin tüm parametreleri, genetik algoritma yaklaşımı kullanılarak belirlenmiştir. Sonuçlar, gecikmeli rezonatörü entegre etmenin süspansiyon sisteminin performansını önemli ölçüde iyileştirdiğini göstermektedir. Sistemin ivme, hız ve konum değişkenlerini kapsayan uygulanan kuvvet, kapsamlı olduğu için her koşulda başarılı olma kapasitesine sahiptir. Bu kapsamlı kontrolör, kontrol sisteminin başarılı bir şekilde çalışması için hayati öneme sahiptir.

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References

  • Avinash, K. S., Chauhan, M., Mall, S.,Karthik, K. S. G., Banik, T. and Dogra, S., 2020. A Review on suspension system design. Journal of Emerging Technologies and Innovative Research, 7(11), 569-574.
  • Caner, M. and Gülseren, U., 2010. Genetik Algoritma ile Fuzzy PSS’in Kural Tablosu Optimizasyonu. Afyon Kocatepe University Journal of Science and Engineering, 1, 83-92.
  • Cronin, D.L., 1981. MacPherson Strut Kinematics. Mechanism and Machine Theory, 16(6), 631-644. https://doi.org/10.1016/0094-114X(81)90069-0
  • Eser, O., Çakan, A., Botsalı, F.M. and Kalyoncu, M., 2021. Arı Algoritması (AA) ve Parçacık Sürü Optimizasyonu (PSO) Kullanarak Çeyrek Araç Modeli Tasarım Parametrelerinin Belirlenmesi. Konya Journal of Engineering Sciences, 9(3), 621-632. https://doi.org/10.36306/konjes.881062
  • Goyal, A. and Sharma, A., 2017. Advances in Active Suspension Sytem. International Conference Proceeding, 2017, 177-181.
  • Huba, M., Chamraz, S., Bistak, P. and Vrancic, D., 2021. Making the PI and PID Controller Tuning Inspired by Ziegler and Nichols Precise and Reliable. Sensors, 21, 6157. https://doi.org/10.3390/s21186157 ISO 8608:2016. Road Profile.
  • Karaman, V. and Kayisli, K., 2017. Sliding Mode Control of Vehicle Suspension System Under Different Road Conditions. International Journal of Engineering Science and Application, 1(2), 72-77.
  • Koulocheris, D., Papaioannou, G. and Chrysos, E., 2017. A comparison of optimal semi-active suspension systems regarding vehicle ride comfort. Materials Science and Engineering, 252, 012022. https://www.doi.org/10.1088/1757-899X/252/1/012022
  • Mutlu, A., 2023. Robust Control with Fuzzy Based Neural Network for Robot Manipulators. International Scientific Journal “Industry 4.0”, 2, 42-46.
  • Olgac, N. and Hansen, T. H., 1994. A novel active vibration absorption technique: Delayed Resonator. Journal of Sound and Vibration, 176(1), 93-104. https://doi.org/10.1006/jsvi.1994.1360
  • Palanisamy, S. and Karuppan, S., 2016. Fuzzy control of active suspension system. Journal of Vibroengineering, 18(5), 3197-3204. https://doi.org/10.21595/jve.2016.16699
  • Shimatani, H., Murata, S., Watanabe, K., Kaneko, T. And Sakai, H., 1999. Development of Torsion Beam Rear Suspension with Toe Control Links. Journal of Passenger Cars, 108(6), 18-22. https://doi.org/10.4271/1999-01-0045
  • Smith, M.C. and Swift, S.J., 2016. Design of passive vehicle suspensions for maximal least damping ratio. Vehicle System Dynamics, 54(5), 568-584. https://doi.org/10.1080/00423114.2016.1145242
  • Şahin, E. and Ayas, M.S., 2019. Performance Analysis of Error-Based and User-Defined Objective Functions for a Particle Swarm Optimization Tuned PID Controller with Derivative Filter. Afyon Kocatepe University Journal of Science and Engineering, 19, 682-689. https://doi.org/10.35414/akufemubid.520823
  • Vignesh, B.S., Ahmed, S., Chandan, V. and Shrivastava, P.K., 2019. Double Wishbone Suspension System; A research. International Journal of Recent Technology and Engineering, 8(2), 5033-5037. http://www.doi.org/10.35940/ijrte.B1084.078219

Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm

Year 2024, , 189 - 196, 27.02.2024
https://doi.org/10.35414/akufemubid.1330683

Abstract

This study utilized a quarter vehicle model and implemented a delayed resonator control approach to regulate the active suspension system. In contrast to the conventional delayed resonator, the force signal in this study is generated through the implementation of the position, velocity, and acceleration delayed resonator. The all parameters of the delayed resonator controller were determined using the genetic algorithm approach. The results suggest that integrating the delayed resonator significantly improves the performance of the suspension system. The applied force, which encompasses acceleration, velocity, and position variables of the system, remains stable under all conditions. This comprehensive controller is vital for the successful operation of the control system.

References

  • Avinash, K. S., Chauhan, M., Mall, S.,Karthik, K. S. G., Banik, T. and Dogra, S., 2020. A Review on suspension system design. Journal of Emerging Technologies and Innovative Research, 7(11), 569-574.
  • Caner, M. and Gülseren, U., 2010. Genetik Algoritma ile Fuzzy PSS’in Kural Tablosu Optimizasyonu. Afyon Kocatepe University Journal of Science and Engineering, 1, 83-92.
  • Cronin, D.L., 1981. MacPherson Strut Kinematics. Mechanism and Machine Theory, 16(6), 631-644. https://doi.org/10.1016/0094-114X(81)90069-0
  • Eser, O., Çakan, A., Botsalı, F.M. and Kalyoncu, M., 2021. Arı Algoritması (AA) ve Parçacık Sürü Optimizasyonu (PSO) Kullanarak Çeyrek Araç Modeli Tasarım Parametrelerinin Belirlenmesi. Konya Journal of Engineering Sciences, 9(3), 621-632. https://doi.org/10.36306/konjes.881062
  • Goyal, A. and Sharma, A., 2017. Advances in Active Suspension Sytem. International Conference Proceeding, 2017, 177-181.
  • Huba, M., Chamraz, S., Bistak, P. and Vrancic, D., 2021. Making the PI and PID Controller Tuning Inspired by Ziegler and Nichols Precise and Reliable. Sensors, 21, 6157. https://doi.org/10.3390/s21186157 ISO 8608:2016. Road Profile.
  • Karaman, V. and Kayisli, K., 2017. Sliding Mode Control of Vehicle Suspension System Under Different Road Conditions. International Journal of Engineering Science and Application, 1(2), 72-77.
  • Koulocheris, D., Papaioannou, G. and Chrysos, E., 2017. A comparison of optimal semi-active suspension systems regarding vehicle ride comfort. Materials Science and Engineering, 252, 012022. https://www.doi.org/10.1088/1757-899X/252/1/012022
  • Mutlu, A., 2023. Robust Control with Fuzzy Based Neural Network for Robot Manipulators. International Scientific Journal “Industry 4.0”, 2, 42-46.
  • Olgac, N. and Hansen, T. H., 1994. A novel active vibration absorption technique: Delayed Resonator. Journal of Sound and Vibration, 176(1), 93-104. https://doi.org/10.1006/jsvi.1994.1360
  • Palanisamy, S. and Karuppan, S., 2016. Fuzzy control of active suspension system. Journal of Vibroengineering, 18(5), 3197-3204. https://doi.org/10.21595/jve.2016.16699
  • Shimatani, H., Murata, S., Watanabe, K., Kaneko, T. And Sakai, H., 1999. Development of Torsion Beam Rear Suspension with Toe Control Links. Journal of Passenger Cars, 108(6), 18-22. https://doi.org/10.4271/1999-01-0045
  • Smith, M.C. and Swift, S.J., 2016. Design of passive vehicle suspensions for maximal least damping ratio. Vehicle System Dynamics, 54(5), 568-584. https://doi.org/10.1080/00423114.2016.1145242
  • Şahin, E. and Ayas, M.S., 2019. Performance Analysis of Error-Based and User-Defined Objective Functions for a Particle Swarm Optimization Tuned PID Controller with Derivative Filter. Afyon Kocatepe University Journal of Science and Engineering, 19, 682-689. https://doi.org/10.35414/akufemubid.520823
  • Vignesh, B.S., Ahmed, S., Chandan, V. and Shrivastava, P.K., 2019. Double Wishbone Suspension System; A research. International Journal of Recent Technology and Engineering, 8(2), 5033-5037. http://www.doi.org/10.35940/ijrte.B1084.078219
There are 15 citations in total.

Details

Primary Language English
Subjects Mechanical Engineering (Other)
Journal Section Articles
Authors

İbrahim Şenaslan 0000-0002-8789-489X

Boğaç Bilgiç 0000-0003-1156-8841

Publication Date February 27, 2024
Submission Date July 21, 2023
Published in Issue Year 2024

Cite

APA Şenaslan, İ., & Bilgiç, B. (2024). Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 24(1), 189-196. https://doi.org/10.35414/akufemubid.1330683
AMA Şenaslan İ, Bilgiç B. Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. February 2024;24(1):189-196. doi:10.35414/akufemubid.1330683
Chicago Şenaslan, İbrahim, and Boğaç Bilgiç. “Control of the Quarter Vehicle Model With an Innovative Delayed Resonator Optimized by Genetic Algorithm”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 24, no. 1 (February 2024): 189-96. https://doi.org/10.35414/akufemubid.1330683.
EndNote Şenaslan İ, Bilgiç B (February 1, 2024) Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 24 1 189–196.
IEEE İ. Şenaslan and B. Bilgiç, “Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm”, Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 24, no. 1, pp. 189–196, 2024, doi: 10.35414/akufemubid.1330683.
ISNAD Şenaslan, İbrahim - Bilgiç, Boğaç. “Control of the Quarter Vehicle Model With an Innovative Delayed Resonator Optimized by Genetic Algorithm”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 24/1 (February 2024), 189-196. https://doi.org/10.35414/akufemubid.1330683.
JAMA Şenaslan İ, Bilgiç B. Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2024;24:189–196.
MLA Şenaslan, İbrahim and Boğaç Bilgiç. “Control of the Quarter Vehicle Model With an Innovative Delayed Resonator Optimized by Genetic Algorithm”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 24, no. 1, 2024, pp. 189-96, doi:10.35414/akufemubid.1330683.
Vancouver Şenaslan İ, Bilgiç B. Control of the Quarter Vehicle Model with an Innovative Delayed Resonator Optimized by Genetic Algorithm. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2024;24(1):189-96.


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