Autopilot Design for an Unmanned Surface Vehicle Based on Backstepping Integral Technique with Experimental Results

Helmi Abrougui , Samir Nejim

Journal of Marine Science and Application ›› 2023, Vol. 22 ›› Issue (3) : 614 -623.

PDF
Journal of Marine Science and Application ›› 2023, Vol. 22 ›› Issue (3) : 614 -623. DOI: 10.1007/s11804-023-00356-4
Research Article

Autopilot Design for an Unmanned Surface Vehicle Based on Backstepping Integral Technique with Experimental Results

Author information +
History +
PDF

Abstract

Controller tuning is the correct setting of controller parameters to control complex dynamic systems appropriately and with high accuracy. Therefore, this study addressed the development of a method for tuning the heading controller of an unmanned surface vehicle (USV) based on the backstepping integral technique to enhance the vehicle behavior while tracking a desired position for water monitoring missions. The vehicle self-steering system (autopilot system) is designed theoretically and tested via a simulation. Based on the Lyapunov theory, the stability in the closed-loop system is guaranteed, and the convergence of the heading tracking errors is obtained. In addition, the designed control law is implemented via a microcontroller and tested experimentally in real time. Conclusion, experimental results were carried out to verify the robustness of the designed controller when disturbances and uncertainties are introduced into the system.

Keywords

Unmanned surface vehicle / Autopilot system design / Control law tuning / Heading controller / Backstepping integral control

Cite this article

Download citation ▾
Helmi Abrougui, Samir Nejim. Autopilot Design for an Unmanned Surface Vehicle Based on Backstepping Integral Technique with Experimental Results. Journal of Marine Science and Application, 2023, 22(3): 614-623 DOI:10.1007/s11804-023-00356-4

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Abrougui H, Nejim S (2018) Backstepping control of an autonomous catamaran sailboat. Robotic Sailing, 41–50

[2]

Abrougui H, Nejim S, Hachicha S, Zaoui C, Dallagi H (2021) Modeling, parameter identification, guidance and control of an unmanned surface vehicle with experimental results. Ocean Engineering, 241, 110038

[3]

Asfihani T, Arif DK, Putra FP, Firmansyah MA. Comparison of LQG and adaptive PID Controller for USV heading control. Journal of Physics: Conference Series, 2019, 1218(1): 012058

[4]

Ashrafiuon H, Muske KR, McNinch LC, Soltan RA. Slidingmode tracking control of surface vessels. IEEE Transactions on Industrial Electronics, 2008, 55(11): 4004-4012

[5]

Bacciotti A, Rosier L (2005) Lyapunov functions and stability in control theory. Springer Science & Business Media

[6]

Bai X, Li B, Xu X, Xiao Y. A review of current research and advances in unmanned surface vehicles. Journal of Marine Science and Application, 2022, 21(2): 47-58

[7]

Bazionis IK, Georgilakis PS. Review of deterministic and probabilistic wind power forecasting: Models, methods, and future research. Electricity, 2021, 2(1): 13-47

[8]

Caccia M, Bibuli M, Bono R, Bruzzone G. Basic navigation, guidance and control of an unmanned surface vehicle. Autonomous Robots, 2008, 25(4): 349-365

[9]

Chen Z, Zhang Y, Zhang Y, Nie Y, Tang J, Zhu S. Disturbance-observer-based sliding mode control design for nonlinear unmanned surface vessel with uncertainties. IEEE Access, 2019, 7: 148522-148530

[10]

Feijóo A, Villanueva D. Assessing wind speed simulation methods. Renewable and Sustainable Energy Reviews, 2016, 56: 473-483

[11]

Fossen TI (2011) Handbook of marine craft hydrodynamics and motion control. John Wiley & Sons

[12]

Gonzalez-Garcia A, Castañeda H. Guidance and control based on adaptive sliding mode strategy for a USV subject to uncertainties. IEEE Journal of Oceanic Engineering, 2021, 46(4): 1144-1154

[13]

Hearn GE, Zhang Y, Sen P. Alternative designs of neural network-based autopilots: a comparative study. IFAC Proceedings Volumes, 1997, 30(22): 83-88

[14]

Hu SS, Juang JY (2011) Robust nonlinear ship course-keeping control under the influence of high wind and large wave disturbances. 8th Asian Control Conference, 393–398

[15]

Jeng DS, Ye JH, Zhang JS, Liu PF. An integrated model for the wave-induced seabed response around marine structures: Model verifications and applications. Coastal Engineering, 2013, 72: 1-19

[16]

Liu L, Wang D, Peng Z, Li T. Modular adaptive control for LOS-based cooperative path maneuvering of multiple underactuated autonomous surface vehicles. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(7): 1613-1624

[17]

Ma LY, Xie W, Huang HB. Convolutional neural network-based obstacle detection for unmanned surface vehicle. Mathematical Biosciences and Engineering, 2019, 17(1): 845-861

[18]

Park JH, Shim HW, Jun BH, Kim SM, Lee PM, Lim YK (2010) A model estimation and multi-variable control of an unmanned surface vehicle with two fixed thrusters. Oceans’10, Sydney, 1–5

[19]

Phanthong T, Maki T, Ura T, Sakamaki T, Aiyarak P. Application of A* algorithm for real-time path re-planning of an unmanned surface vehicle avoiding underwater obstacles. Journal of Marine Science and Application, 2014, 13(1): 105-116

[20]

Qi J, Peng Y, Wang H, Han J (2007) Design and implement of a trimaran unmanned surface vehicle system. 2007 International Conference on Information Acquisition, 361–365

[21]

Sharma SK, Naeem W, Sutton R. An autopilot based on a local control network design for an unmanned surface vehicle. J. Navigation, 2012, 65(2): 281-301

[22]

Sharma SK, Sutton R, Motwani A, Annamalai A. Non-linear control algorithms for an unmanned surface vehicle. Proceedings of the Institution of Mechanical Engineers, Part M, Journal of Engineering for the Maritime Environment, 2013, 227(4): 1-10

[23]

Siramdasu Y, Fahimi F (2012) Incorporating input saturation for underactuated surface vessel trajectory tracking control. American Control Conference, Montreal, 6203–6208

[24]

Song L, Xu C, Hao L, Yao J, Guo R. Research on PID parameter tuning and optimization based on SAC-Auto for USV path following. Journal of Marine Science and Engineering, 2022, 10(12): 1847

[25]

Wang L, Ackermann J (1998) Robustly stabilizing PID controllers for car steering systems. Proceedings of the 1998 American Control Conference, Philadelphia, 1, 41–42. DOI: https://doi.org/10.1109/ACC.1998.694624

[26]

Winursito A, Dhewa OA, Nasuha A, Pratama GN (2022) Integral state feedback controller with coefficient diagram method for USV heading control. 5th International Conference on Information and Communications Technology, 295–300

[27]

Zhang W, Xu Y, Xie J (2019) Path planning of USV based on improved hybrid genetic algorithm. European Navigation Conference, Warsaw, 1–7. DOI: https://doi.org/10.1109/EURONAV.2019.8714160

AI Summary AI Mindmap
PDF

120

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/