Finite-Time PLOS-Based Integral Sliding-Mode Adaptive Neural Path Following for Unmanned Surface Vessels With Unknown Dynamics and Disturbances

Unmanned surface vessels (USVs) are supposed to be able to adapt unstructured environments by means of multi-sensor active perception without any human interference, and high-accuracy path following is achieved for USVs by effective control strategies and intelligent devices of e-navigation. This paper proposes a finite-time predictor line-of-sight (LOS)-based integral sliding-mode adaptive neural (FPISAN) scheme for the path following of USVs in the presence of unknown dynamics and external disturbances, which copies with the problem of merging with the kinematic level and the kinetic level of USVs. From the point of view of USVs’ practical engineering, the inertia matrix of USVs maintains nonzero off-diagonal. In order to ensure that USVs can converge to and follow a defined path, a novel LOS-based guidance law that can acquire sideslip angles by error predictors within a finite time is presented, called finite-time predictor-based LOS (FPLOS). Then, the path-following control laws are designed by combining the neural network (NN) technique with the integral sliding-mode method, where radial basis function NN (RBFNN) is applied to approximate lumped unknown dynamics induced by nonparametric uncertainties and external disturbances. The theoretical analysis verifies that the path-following guidance-control system of USVs is semiglobally uniformly ultimately bounded (SGUUB) with the aid of Lyapunov stability theory. The effectiveness and performance of this presented scheme are illustrated by simulation experiments with the comparison. Note to Practitioners—The design of heading guidance laws and path-following control laws for path following of USVs subject to unknown dynamics and external disturbances is a critical problem, which affects the development of USVs. This problem associated with practical engineering of USVs due to the actual navigation environment that is complex, diversified, and highly unstructured. This paper presents a wholly tight strategy to compensate for unknown sideslip angles and approximate lumped unknown dynamics. Hence, an effective scheme being denoted FPISAN mentioned above is developed for path following of USVs.

[1]  Roger Skjetne,et al.  Robust output maneuvering for a class of nonlinear systems , 2004, Autom..

[2]  Dan Wang,et al.  ESO-Based Line-of-Sight Guidance Law for Path Following of Underactuated Marine Surface Vehicles With Exact Sideslip Compensation , 2017, IEEE Journal of Oceanic Engineering.

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

[4]  Liang Sun,et al.  Path following control for marine surface vessel with uncertainties and input saturation , 2016, Neurocomputing.

[5]  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.

[6]  Weidong Zhang,et al.  Practical proportional integral sliding mode control for underactuated surface ships in the fields of marine practice , 2017 .

[7]  Yuqiang Wu,et al.  Switching-based asymptotic stabilisation of underactuated ships with non-diagonal terms in their system matrices , 2015 .

[8]  Shuzhi Sam Ge,et al.  Direct Adaptive Neural Control for a Class of Uncertain Nonaffine Nonlinear Systems Based on Disturbance Observer , 2013, IEEE Transactions on Cybernetics.

[9]  Roger Skjetne,et al.  Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory , 2005, Autom..

[10]  Hao Wang,et al.  Predictor-based LOS guidance law for path following of underactuated marine surface vehicles with sideslip compensation , 2016 .

[11]  Chao Yang,et al.  Robotic grasping using visual and tactile sensing , 2017, Inf. Sci..

[12]  Tieshan Li,et al.  Path following of underactuated surface vessels with fin roll reduction based on neural network and hierarchical sliding mode technique , 2015, Neural Computing and Applications.

[13]  Miroslav Krstic,et al.  Nonlinear and adaptive control de-sign , 1995 .

[14]  Di Guo,et al.  Deep vision networks for real-time robotic grasp detection , 2016 .

[15]  Di Guo,et al.  Weakly Paired Multimodal Fusion for Object Recognition , 2018, IEEE Transactions on Automation Science and Engineering.

[16]  Kristin Ytterstad Pettersen,et al.  Global uniform asymptotic stabilization of an underactuated surface vessel , 2002, IEEE Trans. Autom. Control..

[17]  Shen Zhi-peng.  Survey for motion control of underactuated surface vessels , 2009 .

[18]  Dennis S. Bernstein,et al.  Finite-Time Stability of Continuous Autonomous Systems , 2000, SIAM J. Control. Optim..

[19]  Kristin Y. Pettersen,et al.  Line-of-Sight Path Following for Dubins Paths With Adaptive Sideslip Compensation of Drift Forces , 2015, IEEE Transactions on Control Systems Technology.

[20]  Yaonan Wang,et al.  Adaptive RBFNNs/integral sliding mode control for a quadrotor aircraft , 2016, Neurocomputing.

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

[22]  Lu Liu,et al.  Path following of marine surface vehicles with dynamical uncertainty and time-varying ocean disturbances , 2016, Neurocomputing.

[23]  Ahmad Bagheri,et al.  Simulation and tracking control based on neural-network strategy and sliding-mode control for underwater remotely operated vehicle , 2009, Neurocomputing.

[24]  Khac Duc Do,et al.  Underactuated ships follow smooth paths with Integral actions and without velocity measurements for feedback: theory and experiments , 2006, IEEE Transactions on Control Systems Technology.

[25]  Sanjay Sharma,et al.  Finite-Time Observer Based Guidance and Control of Underactuated Surface Vehicles With Unknown Sideslip Angles and Disturbances , 2018, IEEE Access.

[26]  Khoshnam Shojaei,et al.  Line-of-Sight Target Tracking Control of Underactuated Autonomous Underwater Vehicles , 2017 .

[27]  Long Cheng,et al.  Adaptive neural network tracking control for manipulators with uncertain kinematics, dynamics and actuator model , 2009, Autom..

[28]  Ning Wang,et al.  Adaptive Robust Finite-Time Trajectory Tracking Control of Fully Actuated Marine Surface Vehicles , 2016, IEEE Transactions on Control Systems Technology.

[29]  Zhihong Man,et al.  Continuous finite-time control for robotic manipulators with terminal sliding mode , 2003, Autom..

[30]  Ma Baoli,et al.  Global Asymptotic Trajectory Tracking and Point Stabilization of Asymmetric Underactuated Ships with Non-Diagonal Inertia/Damping Matrices , 2013 .

[31]  Wenjing Xie,et al.  Global trajectory tracking control of underactuated surface vessels with non-diagonal inertial and damping matrices , 2018 .

[32]  Anastasios M. Lekkas,et al.  Direct and indirect adaptive integral line‐of‐sight path‐following controllers for marine craft exposed to ocean currents , 2017 .

[33]  Guang Li,et al.  Adaptive Control of a Marine Vessel Based on Reinforcement Learning , 2018, 2018 37th Chinese Control Conference (CCC).

[34]  Guoqing Zhang,et al.  Adaptive neural path-following control for underactuated ships in fields of marine practice , 2015 .

[35]  Lionel Lapierre,et al.  Nonsingular path following control of a unicycle in the presence of parametric modelling uncertainties , 2006 .

[36]  Bong Seok Park,et al.  Neural network-based output feedback control for reference tracking of underactuated surface vessels , 2017, Autom..

[37]  Khoshnam Shojaei,et al.  Neural adaptive robust control of underactuated marine surface vehicles with input saturation , 2015 .

[38]  K. D. Do,et al.  Global tracking control of underactuated ships with nonzero off-diagonal terms in their system matrices , 2005, Autom..

[39]  Zhongjiu Zheng,et al.  Finite-Time Sideslip Observer-Based Adaptive Fuzzy Path-Following Control of Underactuated Marine Vehicles with Time-Varying Large Sideslip , 2018, Int. J. Fuzzy Syst..

[40]  Awantha Jayasiri,et al.  Dynamic Positioning of Vessels Using a UKF-Based Observer and an NMPC-Based Controller , 2017, IEEE Transactions on Automation Science and Engineering.

[41]  Thor I. Fossen,et al.  Integral LOS Path Following for Curved Paths Based on a Monotone Cubic Hermite Spline Parametrization , 2014, IEEE Transactions on Control Systems Technology.