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

Yıl 2024, , 189 - 196, 27.02.2024

İbrahim Şenaslan , Boğaç Bilgiç

https://doi.org/10.35414/akufemubid.1330683

Öz

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.

Anahtar Kelimeler

Gecikmeli Rezonatör, Genetik Algoritma, Aktif Süspansiyon Sistemleri, Çeyrek Araç Modeli

Destekleyen Kurum

Yok.

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

Öz

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.

Anahtar Kelimeler

Delayed Resonator, Genetic Algorithm, Active Suspension System, Quarter Car Model

Kaynakça

• 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