Otonom sualtı aracı yörünge izleme kontrol algoritmalarının analizleri

Abstract

Bu çalışmada, bir operatör tarafından direk olarak yönlendirilmeden görevlendirildikleri çalışma alanında özerk hareket ederek görevlerini yerine getiren sualtı araçları için parametre bozulmasının varlığı altında yatay düzlemde yörünge izleme problemi ele alınmıştır. Belirlenen bir yörüngenin takip edilmesi probleminde, literatürde sıkça kullanılan PD denetleyicinin yanı sıra geriadımlamalı denetleyici, kayan kipli denetleyici ve doğrusal karesel regülatör kullanımı önerilmiş olup, bu denetleyici yapılarının performansları sinüzaoidal bir yörünge üzerinde test edilmiştir. Önerilen denetleyicilerin literatürdeki denetleyicilere göre yüksek hassasiyete sahip, parazit önleme ve hızlı tepki vermesi sağlanarak performanslarını gerçekleştirmesi sağlanmıştır. Son olarak, geriadımlamalı ve kayan kipli denetleyicinin kararlılığını kanıtlamak için Lyapunov’un kararlılık ilkesi kullanılarak sistemin kararlı davranışı simülasyon üzerinde gösterilmiştir. Simülasyon ortamında tüm önerilen denetleyicilerin aynı bozucu etki altında istenilen yörüngeyi takip ettiği doğrulanmıştır. Ayrıca önerilen geriadımlamlı denetleyicisindeki keskin geçişler kayan kipli kontrolcü ile giderilmiş ve sistem üzerinde meydana gelebilecek olası arızaların önüne geçilmiştir.

Keywords

• Otonom sualtı araçları
• Geriadımlamalı kontrol
• Kayan kipli kontrol
• Doğrusal karesel regülatör
• Oransal türevsel (PD)kontrol

Analyses of autonomous underwater vehicle trajectory tracking control algorithms

Abstract

In this study, the horizontal trajectory tracking problem under the presence of parameter distortion is discussed for underwater vehicles that perform their duties autonomously in the work area where they are assigned without being directly guided by an operator. In the problem of following a determined trajectory, in addition to the PD controller, which is frequently used in the literature, the use of a backstepping controller, a sliding mode controller and a linear quadratic regulator has been proposed, and the performances of these controller structures have been tested on a sinusoidal trajectory. It has been ensured that the proposed controllers perform with high sensitivity, anti-interference and fast response compared to the controllers in the literature. Finally, the stable behavior of the system is demonstrated on simulation by using Lyapunov's stability principle to prove the stability of the backstepping and sliding mode controller. It has been verified that all proposed controllers follow the desired trajectory under the same disturbance effect in the simulation environment. In addition, the sharp transitions in the proposed backstop controller are eliminated with the sliding mode controller and possible malfunctions that may occur on the system are prevented.

Keywords

• Autonomous underwater vehicles
• Modelling
• Backstepping control
• Sliding mode control
• Linear quadratic regulator control
• Proportional derivative control

References

1. [1] Kumar N, Rani M. “An efficient hybrid approach for trajectory tracking control of autonomous underwater vehicles”. Applied Ocean Research, 95, 1-10, 2020.
2. [2] Elmokadem T, Zribi M, Youcef-Toumi K. “Trajectory tracking sliding mode control of underactuated AUVs”. Nonlinear Dynamics, 84(2), 1079-1091, 2016.
3. [3] Zhang H, Zhang Y, Xu Y, Zhou J, Guo Y. “Research on backstepping tracking control of deep-diving AUV based on biological ınspiration”. IEEE 2020 Chinese Control and Decision Conference (CCDC), Hefei, China, 22-24 August 2020.
4. [4] Lakhwani, DA, Adhyaru, DM. “Performance comparison of PD, PI and LQR controller of autonomous under water vehicle”. IEEE 2013 Nirma University International Conference on Engineering (NUiCONE), Gujarat, India, 28-30 November 2013.
5. [5] Meng F, Liu A, Jing S, Zu Y. “FSM trajectory tracking controllers of OB-AUV in the horizontal plane”. IEEE 2021 International Conference on Intelligence and Safety for Robotics (ISR), Nagoya, Japan, 4-6 March 2021.
6. [6] Li J, Du J, Zhu G, Lewis FL. “Simple adaptive trajectory tracking control of underactuated autonomous underwater vehicles under LOS range and angle constraints”. IET Control Theory & Applications, 14(2), 283-290, 2020.
7. [7] Duan K, Fong S, Chen CP. “Reinforcement learning based model-free optimized trajectory tracking strategy design for an AUV”. Neurocomputing, 469, 289-297,2022.
8. [8] Elmokadem T, Zribi M, Youcef-Toumi K. “Terminal sliding mode control for the trajectory tracking of underactuated Autonomous Underwater Vehicles”. Ocean Engineering, 129, 613-625, 2017.

9. [9] Jiang Y, Guo C, Yu H. “Horizontal trajectory tracking control for an underactuated AUV adopted global integral sliding mode control”. IEEE 2018 Chinese Control and Decision Conference (CCDC), Shenyang, China, 9-11 June 2018.
10. [10] Qiao L, Zhang W. “Fast trajectory tracking control of underactuated autonomous underwater vehicles”. IEEE 2018 8th International Conference on Underwater System Technology: Theory and Applications (USYS), Wuhan, China, 1-3 December 2018.
11. [11] Kang S, Yu J, Zhang J, Hu F. “Research on the trajectory prediction of a twin screw AUV based on an accurate dynamic model”.IEEE 2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE), Dalian, China, 15-17 July 2021.
12. [12] Fossen TI. Guidance and Control of Ocean Vehicles. PhD Thesis, University of Trondheim, Trondheim, Norway, 1999.
13. [13] Fossen TI. Guidance, Navigation, and Control of Ships, Rigs and Underwater Vehicles. 1st ed. Trondheim, Norway, Marine Cybernetics, 2002.
14. [14] Healey AJ, Good MR. “The NPS AUVII Autonomous Underwater Vehicle Testbed: Design and Experimental Verification”. American Society of Naval Engineers, 104(3), 191-202, 1992.
15. [15] Yu C, Xiang X, Niu Z. “3D trajectory tracking for underactuated AUV using guidance-based PD controller”. IEEE 2016 35th Chinese Control Conference (CCC), Chengdu, China, 27-29 July 2016.
16. [16] Krstic M, Kokotovic PV, Kanellakopoulos I. Nonlinear and Adaptive Control Design. 1st ed. USA, John Wiley & Sons, Inc., 1995.
17. [17] Edwards C, Spurgeon S. Sliding Mode Control: Theory and Applications. 1st ed. USA, Crc Press, 1998.
18. [18] Da Silva GRG, Bazanella AS, Lorenzini C, Campestrini L. “Data-driven LQR control design”. IEEE Control Systems Letters, 3(1), 180-185, 2018.
19. [19] Stokey RP, Roup A, von Alt C, Allen B, Forrester N, Austin T, Goldsborough R, Purcell M, Jaffre F, Packard G, Kukulya, A. “Development of the REMUS 600 autonomous underwater vehicle”. IEEE 2005 Proceedings of OCEANS MTS/IEEE, Washington, DC, USA, 17-23 September 2005.
20. [20] Lin JM, Lin CH. “A novel fuel cell system design by using Ziegler-Nichols-based intelligent fuzzy controller”. IEEE 2013 International Conference on Machine Learning and Cybernetics, Tianjin, China, 14-17 July 2013.
21. [21] Gökçen G, Murat F. “PID parameters tuning methods: application to second-order system and evaluation with comparison”. Çukurova University Journal of the Faculty of Engineering and Architecture, 30(2), 355-362, 2015.