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Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi

Year 2023, Volume: 38 Issue: 1, 345 - 356, 21.06.2022

Atilla Bayram Mehmet Nuri Almalı Firas Muhammad Al-naqshbandı

https://doi.org/10.17341/gazimmfd.1024463

Abstract

Bu makalede prototip tasarımı yapılmış olan bir insansız kara aracının yol takip kontrolü konum ve yönelim hata geri beslemesine dayalı olarak sunulmuştur. Bu otonom aracın konum ve yönelimini doğru bir şekilde tanımlamak için aracın ölçme ünitesi gerçek zamanlı küresel yer belirleme sistemi (RTK-GPS), ataletsel ölçme ünitesi (IMU) ve mutlak enkoder sensörlerini içermektedir. Mobil robotun yörünge takibi için ardışık olarak doğrusallaştırılmış ve ayrıklaştırılmış kinematik bir modele dayalı model öngörülü kontrol kullanılmıştır. Bu optimal kontrol metodu verilen bir yol referansı üzerinde hatasız bir şekilde hareket ettiği kabul edilen holonomik olmayan sanal bir araca göre oluşan en küçük konum ve yönel hatalarına ek olarak en düzgün direksiyon açısının elde edilmesi üzerine işlevini gerçekleştirmektedir. Burada takip edilen yollar bir sayısal haritalama programından elde edilen kontrol noktaları ile oluşturulan rasyonel temelli eğriler (spline) veya bilindik geometrik eğriler ile tanımlanmaktadır. Bu makale hem benzetim hem de gerçek zamanlı deneysel test çalışmalarını içermektedir. Elde edilen sonuçlar aracın tasarım performansı ve kontrol stratejisi yönünden irdelenmiştir. Gerçek araç prototipi üzerindeki fiziksel sınırlandırmalara rağmen konum ve yönelim hatalarının makul sınırlar içerisinde oluştuğu gözlemlenmiştir. Özellikle direksiyon açısının aşırı bir salınıma maruz kalmaması kullanılan kontrol metodunun iyi bir performans gösterdiğini ifade etmektedir.

Keywords

İnsansız kara aracı Gerçek araç modelli mobil robot Yol takip kontrolü Gerçek zamanlı kinematik küresel yer belirleme sistemi (RTK-GPS) Modell öngörülü kontrol.

Supporting Institution

VAN Yüzüncü Yıl Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi

Project Number

FBA-2016-5062

Thanks

Bu araştırma, VAN Yüzüncü Yıl Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi tarafından FBA-2016-5062 nolu proje kapsamında desteklenmiş olup katkılarından dolayı teşekkürlerimizi sunarız.

References

  • Bayar G., Long distance autonomous trajectory tracking for an orchard vehicle. Industrial Robot: An International Journal, 40(1), 27-40, 2013.
  • Bogue R. (2016), "Growth in e-commerce boosts innovation in the warehouse robot market", Industrial Robot, 43(6), 583-587, 2016.
  • HAVELSAN, Unmanned ground vehicle (UGV), Barkan https://www.havelsan.com.tr/en/news/daily/unmanned-ground-vehicle-ugv-barkan-will-soon-be-on-the-field, Erişim tarihi:07.11.2021.
  • Mars Exploration Rovers, NASA, https://mars.nasa.gov/mer/index.cfm, Erişim tarihi:05.11.2021.
  • Kıvanç Ö.C., Mungan, T.E., Atila, B.,Tosun, G., An integrated approach to development of unmanned ground vehicle: design, analysis, implementation and suggestion,. Journal of the Faculty of Engineering and Architecture of Gazi University, 34(4), 1957-1973, 2019.
  • Rezaei, S., Sengupta, R., Kalman filter-based integration of DGPS and vehicle sensors for localization. IEEE transactions on control systems technology, 15(6), 1080-1088, 2007.
  • Soetanto D., Lapierre L., Pascoal, A., Adaptive, non-singular path-following control of dynamic wheeled robots. In 42nd IEEE international conference on decision and control, 2, 1765-1770, 2003.
  • Keighobadi J., Menhaj M.B., From nonlinear to fuzzy approaches in trajectory tracking control of wheeled mobile robots, Asian Journal of Control, 14(4), 960-973, 2012.
  • Yang K., Tang X., Qin Y., Huang Y., Wang H., Pu, H., Comparative study of trajectory tracking control for automated vehicles via model predictive control and robust H-infinity state feedback control, Chinese Journal of Mechanical Engineering, 34(1), 1-14, 2021.
  • Jin T.S., Tack H.H., Path following control of mobile robot using Lyapunov techniques and PID controller, International Journal of Fuzzy Logic and Intelligent Systems, 11(1), 49-53, 2011.
  • Solea R., Nunes U. Trajectory planning and sliding-mode control based trajectory-tracking for cybercars, Integrated Computer-Aided Engineering, 14(1), 33-47, 2007.
  • Dang T.S., Duong D.T., Le V.C., Banerjee S., A combined backstepping and adaptive fuzzy PID approach for trajectory tracking of autonomous mobile robots, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43(3), 1-13, 2021.
  • Almayyahi A., Wang W., Hussein A.A. Birch P., Motion control design for unmanned ground vehicle in dynamic environment using intelligent controller, International Journal of Intelligent Computing and Cybernetics, 10(4), 530-548, 2017.
  • Elsheikh E.A., El-Bardini M.A.i Fkirin M.A., Practical path planning and path following for a non-holonomic mobile robot based on visual servoing, In 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, 401-406, 2016.
  • Yu Y., Guo C.,Yu H., Finite-time predictor line-of-sight–based adaptive neural network path following for unmanned surface vessels with unknown dynamics and input saturation, International Journal of Advanced Robotic Systems, 15(6), 1-14, 2018.
  • Singh M.K., Parhi D.R., Path optimization of a mobile robot using an artificial neural network controller, International Journal of Systems Science, 42(1), 107-120, 2011.
  • Cherubini A., Chaumette F., Oriolo G., Visual servoing for path reaching with nonholonomic robots, Robotica, 29(7), 1037-1048, 2011.
  • Zhang Z., Wu Z., Rincon D., Garcia C., Christofides P.D., Operational safety of chemical processes via Safeness-Index based MPC: Two large-scale case studies, Computers & Chemical Engineering, 125, 204-215, 2019.
  • Joe J., Karava P., A model predictive control strategy to optimize the performance of radiant floor heating and cooling systems in office buildings, Applied Energy, 245, 65-77, 2019.
  • Zhao C., Wang D., Hu J., Pan Q., Nonlinear model predictive control-based guidance algorithm for quadrotor trajectory tracking with obstacle avoidance, Journal of Systems Science and Complexity, 34(4), 1379-1400, 2021.
  • Dai L., Yu Y., Zhai D.H., Huang T., Xia Y., Robust model predictive tracking control for robot manipulators with disturbances, IEEE Transactions on Industrial Electronics, 68(5), 4288-4297, 2020.
  • Klaučo M., Kaluz M., Kvasnica M., Real-time implementation of an explicit MPC-based reference governor for control of a magnetic levitation system, Control Engineering Practice, 60, 99-105, 2017.
  • Kuhne F., Lages W.F., da Silva Jr, J.G., Model predictive control of a mobile robot using linearization, In Proceedings of mechatronics and robotics, 525-530, 2004.
  • Lages W.F., Alves J.A.V., Real-time control of a mobile robot using linearized model predictive control, IFAC Proceedings Volumes, 39(16), 968-973, 2006.
  • Guo H., Cao D., Chen H., Sun Z., Hu Y., Model predictive path following control for autonomous cars considering a measurable disturbance: Implementation, testing, and verification, Mechanical Systems and Signal Processing, 118, 41-60, 2019.
  • Kanjanawanishkul K., Hofmeister M., Zell A. Path following with an optimal forward velocity for a mobile robot. IFAC Proceedings Volumes, 43(16), 19-24, 2010.

Year 2023, Volume: 38 Issue: 1, 345 - 356, 21.06.2022

Atilla Bayram Mehmet Nuri Almalı Firas Muhammad Al-naqshbandı

https://doi.org/10.17341/gazimmfd.1024463

Abstract

Project Number

FBA-2016-5062

References

  • Bayar G., Long distance autonomous trajectory tracking for an orchard vehicle. Industrial Robot: An International Journal, 40(1), 27-40, 2013.
  • Bogue R. (2016), "Growth in e-commerce boosts innovation in the warehouse robot market", Industrial Robot, 43(6), 583-587, 2016.
  • HAVELSAN, Unmanned ground vehicle (UGV), Barkan https://www.havelsan.com.tr/en/news/daily/unmanned-ground-vehicle-ugv-barkan-will-soon-be-on-the-field, Erişim tarihi:07.11.2021.
  • Mars Exploration Rovers, NASA, https://mars.nasa.gov/mer/index.cfm, Erişim tarihi:05.11.2021.
  • Kıvanç Ö.C., Mungan, T.E., Atila, B.,Tosun, G., An integrated approach to development of unmanned ground vehicle: design, analysis, implementation and suggestion,. Journal of the Faculty of Engineering and Architecture of Gazi University, 34(4), 1957-1973, 2019.
  • Rezaei, S., Sengupta, R., Kalman filter-based integration of DGPS and vehicle sensors for localization. IEEE transactions on control systems technology, 15(6), 1080-1088, 2007.
  • Soetanto D., Lapierre L., Pascoal, A., Adaptive, non-singular path-following control of dynamic wheeled robots. In 42nd IEEE international conference on decision and control, 2, 1765-1770, 2003.
  • Keighobadi J., Menhaj M.B., From nonlinear to fuzzy approaches in trajectory tracking control of wheeled mobile robots, Asian Journal of Control, 14(4), 960-973, 2012.
  • Yang K., Tang X., Qin Y., Huang Y., Wang H., Pu, H., Comparative study of trajectory tracking control for automated vehicles via model predictive control and robust H-infinity state feedback control, Chinese Journal of Mechanical Engineering, 34(1), 1-14, 2021.
  • Jin T.S., Tack H.H., Path following control of mobile robot using Lyapunov techniques and PID controller, International Journal of Fuzzy Logic and Intelligent Systems, 11(1), 49-53, 2011.
  • Solea R., Nunes U. Trajectory planning and sliding-mode control based trajectory-tracking for cybercars, Integrated Computer-Aided Engineering, 14(1), 33-47, 2007.
  • Dang T.S., Duong D.T., Le V.C., Banerjee S., A combined backstepping and adaptive fuzzy PID approach for trajectory tracking of autonomous mobile robots, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43(3), 1-13, 2021.
  • Almayyahi A., Wang W., Hussein A.A. Birch P., Motion control design for unmanned ground vehicle in dynamic environment using intelligent controller, International Journal of Intelligent Computing and Cybernetics, 10(4), 530-548, 2017.
  • Elsheikh E.A., El-Bardini M.A.i Fkirin M.A., Practical path planning and path following for a non-holonomic mobile robot based on visual servoing, In 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, 401-406, 2016.
  • Yu Y., Guo C.,Yu H., Finite-time predictor line-of-sight–based adaptive neural network path following for unmanned surface vessels with unknown dynamics and input saturation, International Journal of Advanced Robotic Systems, 15(6), 1-14, 2018.
  • Singh M.K., Parhi D.R., Path optimization of a mobile robot using an artificial neural network controller, International Journal of Systems Science, 42(1), 107-120, 2011.
  • Cherubini A., Chaumette F., Oriolo G., Visual servoing for path reaching with nonholonomic robots, Robotica, 29(7), 1037-1048, 2011.
  • Zhang Z., Wu Z., Rincon D., Garcia C., Christofides P.D., Operational safety of chemical processes via Safeness-Index based MPC: Two large-scale case studies, Computers & Chemical Engineering, 125, 204-215, 2019.
  • Joe J., Karava P., A model predictive control strategy to optimize the performance of radiant floor heating and cooling systems in office buildings, Applied Energy, 245, 65-77, 2019.
  • Zhao C., Wang D., Hu J., Pan Q., Nonlinear model predictive control-based guidance algorithm for quadrotor trajectory tracking with obstacle avoidance, Journal of Systems Science and Complexity, 34(4), 1379-1400, 2021.
  • Dai L., Yu Y., Zhai D.H., Huang T., Xia Y., Robust model predictive tracking control for robot manipulators with disturbances, IEEE Transactions on Industrial Electronics, 68(5), 4288-4297, 2020.
  • Klaučo M., Kaluz M., Kvasnica M., Real-time implementation of an explicit MPC-based reference governor for control of a magnetic levitation system, Control Engineering Practice, 60, 99-105, 2017.
  • Kuhne F., Lages W.F., da Silva Jr, J.G., Model predictive control of a mobile robot using linearization, In Proceedings of mechatronics and robotics, 525-530, 2004.
  • Lages W.F., Alves J.A.V., Real-time control of a mobile robot using linearized model predictive control, IFAC Proceedings Volumes, 39(16), 968-973, 2006.
  • Guo H., Cao D., Chen H., Sun Z., Hu Y., Model predictive path following control for autonomous cars considering a measurable disturbance: Implementation, testing, and verification, Mechanical Systems and Signal Processing, 118, 41-60, 2019.
  • Kanjanawanishkul K., Hofmeister M., Zell A. Path following with an optimal forward velocity for a mobile robot. IFAC Proceedings Volumes, 43(16), 19-24, 2010.
There are 26 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Makaleler
Authors

Atilla Bayram 0000-0002-0071-2206

Mehmet Nuri Almalı 0000-0003-2763-4452

Firas Muhammad Al-naqshbandı This is me 0000-0002-2964-784X

Project Number FBA-2016-5062
Publication Date June 21, 2022
Submission Date November 17, 2021
Acceptance Date February 6, 2022
Published in Issue Year 2023 Volume: 38 Issue: 1

Cite

APA Bayram, A., Almalı, M. N., & Al-naqshbandı, F. M. (2022). Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 38(1), 345-356. https://doi.org/10.17341/gazimmfd.1024463
AMA Bayram A, Almalı MN, Al-naqshbandı FM. Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi. GUMMFD. June 2022;38(1):345-356. doi:10.17341/gazimmfd.1024463
Chicago Bayram, Atilla, Mehmet Nuri Almalı, and Firas Muhammad Al-naqshbandı. “Bir insansız Kara aracının Model öngörü Kontrol Metodu Ile GPS Tabanlı Yol Takibi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 38, no. 1 (June 2022): 345-56. https://doi.org/10.17341/gazimmfd.1024463.
EndNote Bayram A, Almalı MN, Al-naqshbandı FM (June 1, 2022) Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 38 1 345–356.
IEEE A. Bayram, M. N. Almalı, and F. M. Al-naqshbandı, “Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi”, GUMMFD, vol. 38, no. 1, pp. 345–356, 2022, doi: 10.17341/gazimmfd.1024463.
ISNAD Bayram, Atilla et al. “Bir insansız Kara aracının Model öngörü Kontrol Metodu Ile GPS Tabanlı Yol Takibi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 38/1 (June 2022), 345-356. https://doi.org/10.17341/gazimmfd.1024463.
JAMA Bayram A, Almalı MN, Al-naqshbandı FM. Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi. GUMMFD. 2022;38:345–356.
MLA Bayram, Atilla et al. “Bir insansız Kara aracının Model öngörü Kontrol Metodu Ile GPS Tabanlı Yol Takibi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 38, no. 1, 2022, pp. 345-56, doi:10.17341/gazimmfd.1024463.
Vancouver Bayram A, Almalı MN, Al-naqshbandı FM. Bir insansız kara aracının model öngörü kontrol metodu ile GPS tabanlı yol takibi. GUMMFD. 2022;38(1):345-56.