Distributed coordinated tracking control of multiple unmanned surface vehicles under complex marine environments

Abstract In this paper, a coordinated tracking strategy with swarm center identification, self-organized aggregation, collision avoidance and distributed controller design for multiple unmanned surface vehicles (USVs) under complex marine environments including both unknown dynamics and external disturbances is presented. For self-organized aggregation and collision avoidance, a velocity feedback control with the repulsive potential function is employed for each vehicle to match surge velocity and heading angle with its neighbors. To keep all vehicles connected in a group, a virtual swarm center (SC) is simultaneously designed and identified using a consensus algorithm, thereby USVs have global knowledge of the desired trajectory. Aiming to precisely estimate completely unknown dynamics together with external disturbances, a distributed tracking controller based wavelet neural network (WNN) is further proposed within the coordinated tracking strategy. Simulation studies and comprehensive comparisons with conventional NN demonstrate excellent performance of the swarm tracking strategy and superiority of WNN scheme.

[1]  Meng Joo Er,et al.  Self-Constructing Adaptive Robust Fuzzy Neural Tracking Control of Surface Vehicles With Uncertainties and Unknown Disturbances , 2015, IEEE Transactions on Control Systems Technology.

[2]  Magnus Egerstedt,et al.  Containment in leader-follower networks with switching communication topologies , 2011, Autom..

[3]  Weisheng Yan,et al.  Model Predictive Visual Servoing of Fully-Actuated Underwater Vehicles With a Sliding Mode Disturbance Observer , 2019, IEEE Access.

[4]  Xiao Liang,et al.  Three‐dimensional trajectory tracking of an underactuated AUV based on fuzzy dynamic surface control , 2019, IET Intelligent Transport Systems.

[5]  Yen-Chen Liu,et al.  Control of semi-autonomous teleoperation system with time delays , 2013, Autom..

[6]  Jin Bae Park,et al.  Adaptive Dynamic Surface Control of Flexible-Joint Robots Using Self-Recurrent Wavelet Neural Networks , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Lu Liu,et al.  Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design. , 2015, ISA transactions.

[8]  Yongsheng Zhao,et al.  Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances , 2018 .

[9]  Guoqiang Hu,et al.  Time-Varying Formation Tracking for Linear Multiagent Systems With Multiple Leaders , 2017, IEEE Transactions on Automatic Control.

[10]  Mengyin Fu,et al.  Distributed containment control of multi‐agent systems with general linear dynamics in the presence of multiple leaders , 2013 .

[11]  Fei Luo,et al.  Leader–Follower Formation Control of USVs With Prescribed Performance and Collision Avoidance , 2019, IEEE Transactions on Industrial Informatics.

[12]  Stephen A. Billings,et al.  A new class of wavelet networks for nonlinear system identification , 2005, IEEE Transactions on Neural Networks.

[13]  Antonio Loría,et al.  Leader–Follower Formation and Tracking Control of Mobile Robots Along Straight Paths , 2016, IEEE Transactions on Control Systems Technology.

[14]  Changyin Sun,et al.  Adaptive Neural Network Control of a Marine Vessel With Constraints Using the Asymmetric Barrier Lyapunov Function , 2017, IEEE Transactions on Cybernetics.

[15]  Heidar Ali Talebi,et al.  Leader-follower formation control of Autonomous Underwater Vehicles with limited communications , 2011, 2011 IEEE International Conference on Control Applications (CCA).

[16]  Beom Hee Lee,et al.  Power efficient formation configuration for centralized leader–follower AUVs control , 2012 .

[17]  Dan Wang,et al.  Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics , 2013, IEEE Transactions on Control Systems Technology.

[18]  Yoo Sang Choo,et al.  Leader-follower formation control of underactuated autonomous underwater vehicles , 2010 .

[19]  Carlos Silvestre,et al.  Coordinated Path-Following in the Presence of Communication Losses and Time Delays , 2009, SIAM J. Control. Optim..

[20]  Tieshan Li,et al.  Bounded Neural Network Control for Target Tracking of Underactuated Autonomous Surface Vehicles in the Presence of Uncertain Target Dynamics , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[21]  Wen Jiang,et al.  Formation Control of Multiple Unmanned Surface Vehicles Using the Adaptive Null-Space-Based Behavioral Method , 2019, IEEE Access.

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

[23]  Gianmarco Radice,et al.  Close proximity formation flying via linear quadratic tracking controller and artificial potential function , 2015 .

[24]  Xiao Liang,et al.  Swarm control with collision avoidance for multiple underactuated surface vehicles , 2019, Ocean Engineering.

[25]  Laxman M. Waghmare,et al.  Adaptive fuzzy exponential terminal sliding mode controller design for nonlinear trajectory tracking control of autonomous underwater vehicle , 2018 .

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

[27]  Balasaheb M. Patre,et al.  Adaptive fuzzy sliding mode control for robust trajectory tracking control of an autonomous underwater vehicle , 2018, Intell. Serv. Robotics.

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

[29]  Amir G. Aghdam,et al.  Distributed control of a network of single integrators with limited angular fields of view , 2016, Autom..

[30]  E. Oland,et al.  Collision and terrain avoidance for UAVs using the potential field method , 2013, 2013 IEEE Aerospace Conference.

[31]  Colin Bradley,et al.  Sliding mode adaptive neural network control for hybrid visual servoing of underwater vehicles , 2017 .

[32]  Jinfeng Liu,et al.  Distributed Model Predictive Control of Nonlinear Systems Based on Price-Driven Coordination , 2016 .

[33]  Shaocheng Tong,et al.  Adaptive Fuzzy Containment Control of Nonlinear Systems With Unmeasurable States , 2019, IEEE Transactions on Cybernetics.

[34]  Weidong Zhang,et al.  Adaptive cooperative formation control of autonomous surface vessels with uncertain dynamics and external disturbances , 2018, Ocean Engineering.

[35]  Rubo Zhang,et al.  A Novel Distributed and Self-Organized Swarm Control Framework for Underactuated Unmanned Marine Vehicles , 2019, IEEE Access.

[36]  Kun Liu,et al.  Networked Control Systems in the Presence of Scheduling Protocols and Communication Delays , 2014, SIAM J. Control. Optim..

[37]  Yanjun Huang,et al.  Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints , 2017, IEEE Transactions on Vehicular Technology.