Output feedback adaptive control for autopilot design of an unmanned surface vehicle

This paper presents a study on autopilot design for an unmanned surface vehicle subject to dynamical uncertainty, time-varying ocean disturbances and unmeasured yaw rate. An output feedback adaptive steering law is developed based on a state observer and a neural network using iterative updating law. As a result, this approach is able to achieve automatic yaw control in presence of dynamical uncertainty and time-varying ocean disturbances without yaw rate measurement. Using a Lyapunov-Krasovskii functional, it is proven that the error signals are uniformly ultimately bounded. Simulation result is given to show the effectiveness of the proposed method.

[1]  Tieshan Li,et al.  Direct adaptive NN control of ship course autopilot with input saturation , 2011, The Fourth International Workshop on Advanced Computational Intelligence.

[2]  李铁山 Robust adaptive backstepping design for course-keeping control of ship with parameter uncertainty and input saturation , 2012 .

[3]  Tieshan Li,et al.  Robust adaptive backstepping design for course-keeping control of ship with parameter uncertainty and input saturation , 2011, 2011 International Conference of Soft Computing and Pattern Recognition (SoCPaR).

[4]  Job van Amerongen,et al.  Adaptive steering of ships - A model reference approach , 1982, Autom..

[5]  K.M. Junaid,et al.  A Neural Network Based Adaptive Autopilot for Marine Applications , 2006, 2006 IEEE Conference on Cybernetics and Intelligent Systems.

[6]  Swarup Das Applicability of sliding mode control in autopilot design for ship motion control , 2014, International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014).

[7]  Minjie Xue,et al.  Study on fuzzy neural network-based ship autopilot , 2010, 2010 Sixth International Conference on Natural Computation.

[8]  Jinlu Sheng,et al.  A novel adaptive fuzzy autopilot design based on DSC , 2011, 2011 International Conference on Electrical and Control Engineering.

[9]  Leigh McCue,et al.  Handbook of Marine Craft Hydrodynamics and Motion Control [Bookshelf] , 2016, IEEE Control Systems.

[10]  Minh-Duc Le,et al.  A new and effective fuzzy PID autopilot for ships , 2003, Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694).

[11]  Wen Chen,et al.  Simultaneous identification of time-varying parameters and estimation of system states using iterative learning observers , 2007, Int. J. Syst. Sci..

[12]  Thor I. Fossen,et al.  Handbook of Marine Craft Hydrodynamics and Motion Control: Fossen/Handbook of Marine Craft Hydrodynamics and Motion Control , 2011 .