Fault Diagnosis Observer and Fault-Tolerant Control Design for Unmanned Surface Vehicles in Network Environments

This study focuses on the network-based fault estimation and fault-tolerant controller designing for an unmanned surface vehicle submit to actuator faults, along with transmission delays, packet dropouts and packet disordering in the communication network channels between sampler and observer, and between controller and actuator. Compared with manned surface vehicles, unmanned surface vehicles in the network bring certain competitive superiorities as well as challenges. By using an intermediate variable, an observer is devised in network environments to estimate the states and actuator faults of the unmanned surface vehicle simultaneously. A sufficient condition is introduced and proved for the fault observer being uniformly ultimately bounded. Based on the fault observer, a fault-tolerant controller is proposed, which can ensure that the network-based closed-loop control system is uniformly ultimately bounded theoretically. Theoretical analysis and simulation results verify the performance of the fault observer and fault-tolerant control in network environments for an unmanned surface vehicle.

[1]  Tor A. Johansen,et al.  Dynamic Positioning System as Dynamic Energy Storage on Diesel-Electric Ships , 2014, IEEE Transactions on Power Systems.

[2]  Qing-Long Han,et al.  Network-Based Fault Detection Filter and Controller Coordinated Design for Unmanned Surface Vehicles in Network Environments , 2016, IEEE Transactions on Industrial Informatics.

[3]  Wenwen Liu,et al.  A Robust Localization Method for Unmanned Surface Vehicle (USV) Navigation Using Fuzzy Adaptive Kalman Filtering , 2019, IEEE Access.

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

[5]  Arnau Doria-Cerezo,et al.  Passivity-based control applied to the dynamic positioning of ships , 2012 .

[6]  Hak-Keung Lam,et al.  Observer-Based Fuzzy Control for Nonlinear Networked Systems Under Unmeasurable Premise Variables , 2016, IEEE Transactions on Fuzzy Systems.

[7]  Xin Xu,et al.  Collision Avoidance Planning Method of USV Based on Improved Ant Colony Optimization Algorithm , 2019, IEEE Access.

[8]  Jun Wang,et al.  Distributed Containment Maneuvering of Multiple Marine Vessels via Neurodynamics-Based Output Feedback , 2017, IEEE Transactions on Industrial Electronics.

[9]  Qing-Long Han,et al.  Network-Based T–S Fuzzy Dynamic Positioning Controller Design for Unmanned Marine Vehicles , 2018, IEEE Transactions on Cybernetics.

[10]  Yang Liu,et al.  Least-Squares Fault Detection and Diagnosis for Networked Sensing Systems Using A Direct State Estimation Approach , 2013, IEEE Transactions on Industrial Informatics.

[11]  Thor I. Fossen,et al.  Genetic Programming for the Automatic Design of Controllers for a Surface Ship , 2008, IEEE Transactions on Intelligent Transportation Systems.

[12]  Yun Li,et al.  Self-Adaptive Dynamic Obstacle Avoidance and Path Planning for USV Under Complex Maritime Environment , 2019, IEEE Access.

[13]  Yu Wang,et al.  Path Generation of Autonomous Approach to a Moving Ship for Unmanned Vehicles , 2015, IEEE Transactions on Industrial Electronics.

[14]  Hitoshi Katayama,et al.  Straight-Line Trajectory Tracking Control for Sampled-Data Underactuated Ships , 2014, IEEE Transactions on Control Systems Technology.

[15]  Dan Wang,et al.  Containment Maneuvering of Marine Surface Vehicles With Multiple Parameterized Paths via Spatial-Temporal Decoupling , 2017, IEEE/ASME Transactions on Mechatronics.

[16]  Dongkyoung Chwa,et al.  Global Tracking Control of Underactuated Ships With Input and Velocity Constraints Using Dynamic Surface Control Method , 2011, IEEE Transactions on Control Systems Technology.

[17]  Bingbing Qiu,et al.  A Formation Collision Avoidance System for Unmanned Surface Vehicles With Leader-Follower Structure , 2019, IEEE Access.

[18]  Asgeir J. Sørensen,et al.  Robust Dynamic Positioning of Offshore Vessels Using Mixed-μ Synthesis Modeling, Design, and Practice , 2017 .

[19]  Zao-Jian Zou,et al.  A two-time scale control law based on singular perturbations used in rudder roll stabilization of ships , 2014 .

[20]  Xiangpeng Xie,et al.  Observer-Based Non-PDC Control for Networked T–S Fuzzy Systems With an Event-Triggered Communication , 2017, IEEE Transactions on Cybernetics.

[21]  Yong-Kon Lim,et al.  Point-to-point navigation of underactuated ships , 2008, Autom..

[22]  Miroslav Krstic,et al.  Robust dynamic positioning of ships with disturbances under input saturation , 2016, Autom..

[23]  Qing-Long Han,et al.  Network-Based Heading Control and Rudder Oscillation Reduction for Unmanned Surface Vehicles , 2017, IEEE Transactions on Control Systems Technology.

[24]  T.I. Fossen,et al.  Kalman filtering for positioning and heading control of ships and offshore rigs , 2009, IEEE Control Systems.

[25]  Zhu Qidan,et al.  Sliding mode tracking control of an underactuated surface vessel , 2012 .

[26]  Bingbing Qiu,et al.  Adaptive Course Control-Based Trajectory Linearization Control for Uncertain Unmanned Surface Vehicle Under Rudder Saturation , 2019, IEEE Access.

[27]  Zheng Yan,et al.  Model Predictive Control for Tracking of Underactuated Vessels Based on Recurrent Neural Networks , 2012, IEEE Journal of Oceanic Engineering.

[28]  Petros A. Ioannou,et al.  Adaptive steering control for uncertain ship dynamics and stability analysis , 2013, Autom..

[29]  Huijun Gao,et al.  Fault Detection for Discrete Systems With Network-Induced Nonlinearities , 2014, IEEE Transactions on Industrial Informatics.