Research On Modeling And Motion Control Strategy For Single Stern Propulsion Unmanned Surface Vehicle

Unmanned surface vehicle(USV)is a kind of marine intelligent motion platform which can sail safely and autonomously in the water environment and accomplish various tasks.The application range of USV is very wide.In the civilian field,it can be used for water quality monitoring,exploration and rescue,etc.;in the military field,it can undertake different combat missions by equipping different mission modules.In the highly dynamic and unpredictable marine environment,the control of the USV is the core issue and the important premise for it to complete various complex tasks.The USV needs flexible and reliable maneuverability,precise and fast control ability to ensure its own safe navigation,and its control system should have good adaptability,robustness and strong anti-interference ability.In this dissertation,the theoretical and experimental research on the modeling,course control,path following and trajectory tracking of a single stern propulsion USV is carried out.The main research contents are as follows:(1)Aiming at the modelling problem of single stern propulsion USV,the three degree of freedom model and response model of single stern propulsion are established under reasonable assumptions and certain constraints.The data support is provided by the field experiments(turning test and zig-zag test)carried out by "Lanxin" USV.The parameters of the three degree of freedom model,response model and propeller servo model are obtained by the method of empirical formula and identification modeling,and the identification results are verified.(2)Aiming at the situation of light weight,small volume and easy to be disturbed,a nonlinear feedback course control strategy with strong anti-interference ability is proposed to solve the course control problem of the USV.In severe sea conditions,the nonlinear feedback course control strategy can keep the course of the USV near the target course,and the range of its propulsion angle is smaller and more stable than the standard feedback,which avoids frequent operation of the servo system and reduces energy consumption.In addition,according to the different convergence speed of linear sliding mode and nonsingular terminal sliding mode at the equilibrium point,a fast nonsingular terminal sliding mode course keeping strategy with fast convergence speed is proposed.Then,the Radial Basis Function(RBF)neural network and disturbance observer are used to compensate for unknown dynamics and external disturbances.At the same time,the saturation function and fuzzy weighting are used to reduce the chattering phenomenon to enhance the robustness of the system.The nonlinear feedback course control strategy with strong anti-interference ability is adopted in severe sea conditions,and the sliding mode course control strategy with fast nonsingular terminal is adopted in general sea conditions,which has fast convergence speed and high control accuracy.(3)Aiming at the problem of path following control of USV,an adaptive line of sight(LOS)navigation algorithm based on fuzzy optimization of visual distance is designed on the basis of unknown sideslip angle,and a path following control scheme is proposed by combining with nonlinear feedback course control.Then the feasibility of the proposed control strategy is verified by simulation and field experiment.Based on this,considering the existence of modeling error and external interference,the trajectory linearization control method is introduced into the design of the path following controller of the USV,and the modeling error and external interference are compensated by the minimum learning parameter(MLP)and adaptive technology,which improves the robustness of the control algorithm..(4)Aiming at the problem of trajectory tracking control of USV,taking into account the problems of high uncertainty of parameters,external disturbances and "computation explosion",the RBF neural network and adaptive algorithm are used to compensate for unknown dynamics and external disturbances,respectively.The neural shunt model is introduced into the design of the controller to solve the "computation explosion" problem,and an adaptive trajectory tracking control strategy is proposed.Considering the driving capacity of the USV,the saturation auxiliary design system is introduced to solve the problem of input saturation of the controlled system.The unknown dynamics and external interference are regarded as a whole,and then the neural network MLP method with less computation is used to compensate it,and a trajectory tracking control strategy with less computation is proposed,which has strong robustness and practicability.The stability analysis ensures the stability of the course and track control system,and the simulation research and field experiment verify the effectiveness of the control strategy of the USV.