Hostname: page-component-848d4c4894-wzw2p Total loading time: 0 Render date: 2024-06-11T12:00:16.161Z Has data issue: false hasContentIssue false
  • English
  • Français

Improved Integral LOS Guidance and Path-Following Control for an Unmanned Robot Sailboat via the Robust Neural Damping Technique

Published online by Cambridge University Press:  05 July 2019

Guoqing Zhang ,
Jiqiang Li ,
Bo Li  and
Xianku Zhang
Guoqing Zhang*
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China) (Collaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian, China)
Jiqiang Li
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China)
Bo Li
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China)
Xianku Zhang
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China)
*
(E-mail: zhangxk@dlmu.edu.cn)
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.

Keywords

Path-followingURSIntegral LOS guidanceRobust neural damping technique
Type
Research Article
Information
The Journal of Navigation , Volume 72 , Issue 6 , November 2019 , pp. 1378 - 1398
Copyright
Copyright © The Royal Institute of Navigation 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Abril, J., Salom, J. and Calvo, O. (1997). Fuzzy control of a sailboat. International Journal of Approximate Reasoning, 16(4), 359–375.Google Scholar
Alves, J. C. and Cruz, N. A. (2014). A mission programming system for an autonomous sailboat. Oceans Conference. St Johns, CANADA.Google Scholar
Arredondo-Galeana, A. and Viola, I. M. (2018). The leading-edge vortex of yacht sails. Ocean Engineering, 159, 552–562.Google Scholar
Caharija, W., Pettersen, K. Y., Gravdahl, J. T. and Borhaug, E. (2012). Integral LOS guidance for horizontal path following of underactauted autonomous underwater vehicles in the presence of vertical ocean currents. 2012 American Control Conference. Montreal, Canada.Google Scholar
Carter, W. E. and Carter, M. S. (2010). The age of sail: A time when the fortunes of nations and lives of seamen literally turned with the winds their ships encountered at sea. The Journal of Navigation, 63, 717–731.Google Scholar
Corno, M., Formentin, S. and Savaresi, S. M. (2016). Data-driven online speed optimization in autonomous sailboats. IEEE Transactions on Intelligent Transportation Systems, 17(3), 762–771.Google Scholar
Deng, Y., Zhang, X. and Zhang, G. (2018). Fuzzy logic based speed optimization and path following control for sailassisted ships. Ocean Engineering, 171, 300–310.Google Scholar
Do, K. D. (2010). Practical control of underactuated ships. Ocean Engineering, 37, 1111–1119.Google Scholar
Fossen, T. I. (2011). Handbook of Marine Craft Hydrodynamics and MotionControl. New York, Wiley.Google Scholar
Guo, Y., Romero, M., Ieng, S.-H., Plumet, P., Benosman, R. and Gas, B. (2011). Reactive path planning for autonomous sailboat using an omni-directional camera for obstacle detection. Proceedings of the 2011 IEEE International Conference on Mechatronics. Istanbul, Turkey.Google Scholar
Illingworth, J. H. (1997). Navigation and strategy in ocean racing. The Journal of Navigation, 50(3), 381–389.Google Scholar
Li, T.-S., Wang, D., Feng, G. and Tong, S.-C. (2010). A DSC approach to robust adaptive NN tracking control for strict-feedback nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics, 40(3), 15–27.Google Scholar
Li, Y. and Tong, S. (2018a). Adaptive neural networks prescribed performance control design for switched interconnected uncertain nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 29(7), 3059–3068.Google Scholar
Li, Y. and Tong, S. (2018b). Fuzzy adaptive control design strategy of nonlinear switched large-scale systems. IEEE Transactions on Systems, Man and Cybernetics: Systems, 48(12), 2209–2218.Google Scholar
Perez, T. (2005). Ship Motion Control (Course keeping and roll stabilisation using rudder and fins). London, Springer.Google Scholar
Petres, C., Romero-Ramirez, M.-A. and Plumet, F. (2012). A potential field approach for reactive navigation of autonomous sailboats. Robotics and Autonomous Systems, 6(5), 1520–1527.Google Scholar
Plumet, F., Petres, C., Romero-Ramirez, M.-A., Gas, B. and Ieng, S.-H. (2015). Toward an autonomous sailing boat. IEEE Journal of Oceanic Engineering, 40(2), 397–407.Google Scholar
Qiao, L. and Zhang, W. (2018). Double-Loop Integral Terminal Sliding Mode Tracking Control for UUVs With Adaptive Dynamic Compensation of Uncertainties and Disturbances. IEEE Journal of Oceanic Engineering, 2, 1–25.Google Scholar
Serrano, M. E., Scaglia, G. J. E., Godoy, S. A., Mut, V. and Ortiz, O. A. (2014). Trajectory tracking of underactuated surface vessels: A linear algebra approach. IEEE Transactions on Control System Technology, 22(3), 1103–1111.Google Scholar
Statheros, T., Howells, G. and Maier, K. M. (2008). Autonomous ship collision avoidance navigation concepts, technologies and techniques. The Journal of Navigation, 61(1), 129–142.Google Scholar
Stelzer, R. and Proll, T. (2008). Autonomous sailboat navigation for short course racing. Robotics and Autonomous Systems, 56(7), 604–614.Google Scholar
Tagliaferri, F. and Viola, I. M. (2017). A real-time strategy-decision program for sailing yacht races. Ocean Engineering, 134, 129–139.Google Scholar
Tagliaferri, F., Philpott, A. B., Viola, I. M. and Flay, R. G. J. (2014). On risk attitude and optimal yacht racing tactics. Ocean Engineering, 90(4), 149–254.Google Scholar
Viel, C., Vautier, U., Wan, J. and Jaulin, L. (2018). Position keeping control of an autonomous sailboat. 11th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles (CAMS). Opatijia, Croatia.Google Scholar
Wille, K. L., Hassani, V. and Sprenger, F. (2016). Modeling and course control of sailboats. IFAC PapersOnLine, 49(23), 532–539.Google Scholar
Xiao, K., Sliwka, J. and Jaulin, L. (2011). A wind-independent control strategy for autonomous sailboats based on voronoi diagram. CLAWAR 2011. France.Google Scholar
Xiao, L. and Jouffroy, J. (2014). Modeling and nonlinear heading control of sailing yachts. IEEE Journal of Oceanic Engineering, 39(2), 256–268.Google Scholar
Xu, B. and Shou, Y. (2018). Composite Learning Control of MIMO Systems with Applications. IEEE Transactions on Industrial Electronics, 65(8), 6414–6424.Google Scholar
Xu, B. and Sun, F. (2018). Composite Intelligent Learning Control of Strict-Feedback Systems with Disturbance. IEEE Transactions on Cybernetics, 48(2), 730–741.Google Scholar
Xu, B., Shi, Z., Yang, C. and Sun, F. (2014). Composite Neural Dynamic Surface Control of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form. IEEE Transactions on Cybernetics, 44(12), 2626–2634.Google Scholar
Yeh, E. C. and Bin, J.-C. (1992). Fuzzy control for self-steering of a sailboat. International Conference on Intelligent Control and Instrumentation. Singapore.Google Scholar
Zhang, G. and Zhang, X. (2014). Concise robust adaptive path-following control of under-actuated ships using DSC and MLP. IEEE Journal Ocean Engineering, 39(4), 685–694.Google Scholar
Zhang, G. and Zhang, X. (2015). A novel DVS guidance principle and robust adaptive path following control for underactuated ships using low frequency gain-learning. ISA Transactions, 56, 75–85.Google Scholar
Zhang, G., Deng, Y. and Zhang, W. (2017). Robust neural path-following control for underactuated ships with the DVS obstacles avoidance guidance. Ocean Engineering, 143, 198–208.Google Scholar
Zhang, G., Zhang, X. and Zhang, Y. (2015). Adaptive neural path-following control for underactuated ships in fields of marine practice. Ocean Engineering, 104(8), 558–567.Google Scholar