Path following control of an underactuated unmanned marine vehicle with model asymmetry in the presence of ocean current disturbances

Path following control system of an underactuated unmanned marine vehicle is an important guarantee for its successful operation, the path following control problem of an underactuated and asymmetrical unmanned marine vehicle sailing in the presence of ocean current disturbances is addressed. Asymmetry of the unmanned marine vehicle model and higher order velocity coupling terms of damping coefficients of the unmanned marine vehicle are discussed, which would improve the accuracy of the path following control system. A kind of global differential homeomorphism transformation design is proposed to solve the difficulty of nonzero term appearing in the non-diagonal elements of the system inertia coefficient matrix and damping coefficient matrix, which is caused by the model asymmetry of unmanned marine vehicle. An improved line-of-sight guidance algorithm is presented by introducing longitudinal position error and tracking error weight factor into traditional line-of-sight algorithm, which could speed up the path following process, meanwhile the method could be extended to the application of curve path following. Virtual velocity in the tangent direction of the path to be followed is designed for the control system, by increasing a virtual control input, the underactuated control system is simplified, and the higher order velocity coupling terms of damping coefficients are integrated considered in the virtual control law. Stability of the path following control algorithm proposed for unmanned marine vehicle is proved by Lyapunov theory, and some simulation experiments are carried out to verify the effectiveness of the path following control system designed.

[1]  Tong Ge,et al.  Horizontal path-following control for deep-sea work-class ROVs based on a fuzzy logic system , 2018 .

[2]  Yabin Wang,et al.  Robust exponential point stabilization control of the high-speed underactuated unmanned marine vehicle with model asymmetry , 2019 .

[3]  Guangming Xie,et al.  Yaw-Guided Trajectory Tracking Control of an Asymmetric Underactuated Surface Vehicle , 2019, IEEE Transactions on Industrial Informatics.

[4]  Kristin Ytterstad Pettersen,et al.  Experimental investigation of locomotion efficiency and path-following for underwater snake robots with and without a caudal fin , 2018, Annu. Rev. Control..

[5]  Hai Huang,et al.  Model Based Adaptive Control and Disturbance Compensation for Underwater Vehicles , 2018 .

[6]  Chenglong Wang,et al.  High-Gain Observer-Based Line-of-Sight Guidance for Adaptive Neural Path Following Control of Underactuated Marine Surface Vessels , 2019, IEEE Access.

[7]  Lionel Lapierre,et al.  Nonlinear guidance and fuzzy control for three-dimensional path following of an underactuated autonomous underwater vehicle , 2017 .

[8]  A. Isidori Nonlinear Control Systems , 1985 .

[9]  Feng Ju,et al.  A New Adaptive Time-Delay Control Scheme for Cable-Driven Manipulators , 2019, IEEE Transactions on Industrial Informatics.

[10]  Lihua Xie,et al.  Error-Constrained LOS Path Following of a Surface Vessel With Actuator Saturation and Faults , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[11]  Bai Chen,et al.  Trajectory Tracking Control of Underwater Vehicle-Manipulator System Using Discrete Time Delay Estimation , 2017, IEEE Access.

[12]  Yaoyao Wang,et al.  Practical adaptive fractional‐order nonsingular terminal sliding mode control for a cable‐driven manipulator , 2018, International Journal of Robust and Nonlinear Control.

[13]  Eduardo Lorenzetti Pellini,et al.  Development of an AUV control architecture based on systems engineering concepts , 2018 .

[14]  Ning Wang,et al.  Finite-time observer based accurate tracking control of a marine vehicle with complex unknowns , 2017 .

[15]  Ning Wang,et al.  Backpropagating Constraints-Based Trajectory Tracking Control of a Quadrotor With Constrained Actuator Dynamics and Complex Unknowns , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  Ye Li,et al.  Route optimizing and following for autonomous underwater vehicle ladder surveys , 2018 .

[17]  Ali Mansour,et al.  Fusion of Swath Bathymetric Data: Application to AUV Rapid Environment Assessment , 2019, IEEE Journal of Oceanic Engineering.

[18]  Zhu Qidan,et al.  Path Following Control of Fully Actuated Autonomous Underwater Vehicle Based on LADRC , 2018 .

[19]  Caoyang Yu,et al.  Adaptive Fuzzy Trajectory Tracking Control of an Under-Actuated Autonomous Underwater Vehicle Subject to Actuator Saturation , 2018, Int. J. Fuzzy Syst..

[20]  Xingru Qu,et al.  Three-dimensional trajectory tracking control of an underactuated autonomous underwater vehicle based on ocean current observer , 2018, International Journal of Advanced Robotic Systems.

[21]  Yueying Wang,et al.  Fuzzy Uncertainty Observer-Based Path-Following Control of Underactuated Marine Vehicles with Unmodeled Dynamics and Disturbances , 2018, 2017 International Conference on Fuzzy Theory and Its Applications (iFUZZY).

[22]  Lei Wan,et al.  Serret-Frenet frame based on path following control for underactuated unmanned surface vehicles with dynamic uncertainties , 2015 .

[23]  Peter King,et al.  Teach‐and‐repeat path following for an autonomous underwater vehicle , 2018, J. Field Robotics.

[24]  Xin Yang,et al.  Parameter identification of unmanned marine vehicle manoeuvring model based on extended Kalman filter and support vector machine , 2019 .

[25]  Xin Yang,et al.  Heading Control of Unmanned Marine Vehicles Based on an Improved Robust Adaptive Fuzzy Neural Network Control Algorithm , 2019, IEEE Access.

[26]  Alireza Fathi,et al.  A Low-Cost Dead Reckoning Navigation System for an AUV Using a Robust AHRS: Design and Experimental Analysis , 2018, IEEE Journal of Oceanic Engineering.

[27]  Vincent Creuze,et al.  A nonlinear controller based on saturation functions with variable parameters to stabilize an AUV , 2019 .

[28]  Hongde Qin,et al.  A novel adaptive second order sliding mode path following control for a portable AUV , 2018 .

[29]  Hao Wang,et al.  Globally Stable Adaptive Dynamic Surface Control for Cooperative Path Following of Multiple Underactuated Autonomous Underwater Vehicles , 2018 .

[30]  Pengfei Zhang,et al.  Underwater Terrain Positioning Method Using Maximum a Posteriori Estimation and PCNN Model , 2019, Journal of Navigation.

[31]  Tao Liu,et al.  PATH FOLLOWING CONTROL OF THE UNDERACTUATED USV BASED ON THE IMPROVED LINE-OF-SIGHT GUIDANCE ALGORITHM , 2017 .

[32]  Jesse David,et al.  Coupled Hydroplane and Variable Ballast Control System for Autonomous Underwater Vehicle Altitude-Keeping to Variable Seabed , 2018, IEEE Journal of Oceanic Engineering.

[33]  Modeling Positional Uncertainty for Hydrographic Surveys with AUV , 2019, Journal of Surveying Engineering.

[34]  Zhouhua Peng,et al.  Output-Feedback Path-Following Control of Autonomous Underwater Vehicles Based on an Extended State Observer and Projection Neural Networks , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[35]  Qiang Ma,et al.  Three-Dimensional Path Following of an Underactuated AUV Based on Fuzzy Backstepping Sliding Mode Control , 2018, Int. J. Fuzzy Syst..

[36]  Thor I. Fossen,et al.  Guidance and control of ocean vehicles , 1994 .

[37]  Kristin Ytterstad Pettersen,et al.  Observer Based Path Following for Underactuated Marine Vessels in the Presence of Ocean Currents: A Global Approach - With proofs , 2018, ArXiv.

[38]  Ning Wang,et al.  Fuzzy unknown observer-based robust adaptive path following control of underactuated surface vehicles subject to multiple unknowns , 2019, Ocean Engineering.

[39]  Mohammad Danesh,et al.  Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle , 2019, Applied Ocean Research.