Simulation On Trajectory Control For Unmanned Surface Vessels

As a typical unmanned motion platform,the unmanned surface vessel(USV)has a lot of advantages over manned ships,such as,small volume,high-speed,stealthy,mobile and flexible,no dangerous about casualties,and so on.USV will complete various missions in the ocean,such as environment monitoring,resource reconnaissance,aid succor,surveillance and patrol,which plays an important role in the national ocean security and ocean resource development.Automatization is one of the most important criterions for USV development,and trajectory control is a key technology of USV control system,due to its nonlinear dynamics,multi-variables,channels coupling,parametric perturbation,model uncertainty and external disturbance.Therefore,this thesis studies problem of trajectory control for USV.The main results achieved in this dissertation are summarized as follows.1.The six-degree-of-freedom motion equations of USV are derived,and the dynamics model of USV is given.1)The referenced frames and motion parameters of the USV is defined.2)The kinematics equations are derived by using the coordinate transformation.3)The dynamics model of USV is derived from the Newton-Euler formulation.2.A sliding mode control approach for trajectory tracking control of USV is presented.1)The problem of trajectory tracking is formulated.2)The tracking error and sliding surface are defined,the SMC law is designed to track a referenced trajectory,and the stability of the closed-loop control system is proven by using the Lyapunov stability theorem.3)Simulation results illustrate that USV tracks the referenced trajectory effectively under the SMC despite parametric perturbation and external disturbance.However,the chattering is generated due to the “switching control” of SMC.3.A fuzzy adaptive gain tuning sliding mode control(FAGT-SMC)approach for trajectory tracking control of USV is proposed.1)The chattering problem is analyzed,and the block diagram of FAGT-SMC is depicted.2)To decrease the chattering,a FAGT-SMC is proposed in which the control gains are tuned according to fuzzy rules,with switching sliding surface function and its derivative as fuzzy control inputs and control gains as fuzzy control outputs.3)Simulation results illustrate that the FAGT-SMC performs well in terms of stability and robustness of trajectory tracking control despite model uncertainty and external disturbance.The FAGT-SMC decreases chattering effectively.4.A neural network approximation sliding mode control(NNA-SMC)approach for trajectory tracking control of USV is proposed.1)The problem of model uncertainty is formulated and the block diagram of NNA-SMC is depicted.2)To solve the problem of model uncertainty,a radial basic function neural network(RBFNN)is employed to approximate the uncertain model of the USV.The stability of the closed-loop control system is proven via the Lyapunov stability theorem.The effectiveness of the NNA-SMC is demonstrated via simulation studies.The NNA-SMC improved the adaptability and robustness compared with SMC.This thesis studies the dynamics model and control methods of USV,which provides effective approaches for trajectory control system design of USV.The research work also has high application value in underwater autonomous vehicle,launch vehicle and robotics,and other ocean application projects.