Study On Trajectory Tracking Control Of State-Constrained Unmanned Surface Vessels

As a powerful marine equipment,the unmanned surface vehicle(USV)has shown great research value in both military and civilian fields.In order to ensure that USV can navigate to the specified target according to the expected plan,it is necessary to carry out accurate stateconstrained trajectory tracking control.Based on the barrier Lyapunov function and stability theory,this paper studies the trajectory tracking control problem of state-constrained USV deeply after simplifying the motion model of three degrees of freedom.At the same time,the disturbance uncertainty,actuator saturation,system filtering and chattering reduction,and finite-time convergence are considered to conduct the design and analysis of the control algorithm.The main work of this paper includes the following aspects:Firstly,a new state saturation function is designed based on the traditional ln-type barrier Lyapunov function to cope with the state constraints problem of USV,which can limit the state variables within the preset boundaries.Meanwhile,the combination of dynamic surface control and first-order filter is used to eliminate the chattering and fluctuation phenomenon.Through simulation and comparative analysis,the smooth and stable trajectory tracking of the proposed algorithm is realized.Secondly,a tan-type barrier Lyapunov function which is also suitable for unconstrained case is proposed,it can be utilized to handle USV which sails in the open water when there is no operational mission.At the same time,uncertain nonlinear term is approximated by radial basis function neural network,and the adaptive estimation technique is used to compensate the upper bound square value of relevant unknown variables including external disturbances.In addition,input saturation problem exists in actuator of USV is solved by means of the antiwindup compensation technique combines with auxiliary system,and the influence of saturation difference is eliminated.Numerical simulation is conducted to prove the effectiveness of presented strategy,it is verified that the semi-global asymptotic convergence is guaranteed while realizing constant state constraints and trajectory tracking of USV.Finally,considering the finite-time convergence,a trajectory tracking control scheme with better performance is designed for the state-constrained USV.Based on the constant state constraints,a time-varying tan-type barrier Lyapunov function is constructed to deal with the time-varying external constraints.Besides,the neural network and fuzzy system are considered together,an interval type-2 fuzzy neural network compensator is designed to estimate the strong disturbance nonlinearity in the system.After strict theoretical proof,the simulation results show that USV can track the desired trajectories with high precision and the trajectory tracking errors can converge in a finite time.This paper takes the state constraints of USV as the main research line and designs several trajectory tracking control schemes based on the barrier Lyapunov function.Simulation analyses verify the feasibility and superiority of the proposed control strategies.The results obtain in this paper are expected to provide referential value and pave the way for further research.