Research On Control Method Of Trajectory Tracking For Unmanned Surface Vehicle

The unmanned surface vehicle is a smart platform which can navigate by itself at sea.It can respond quickly to the changes of environment and it has the advantages of lightweight,functional,the advantages of the high speed.The unmanned surface vehicle has a strong ability to adapt to harsh conditions and has been widely used in military and civil service.At the same time,it is very important for the unmanned surface vehicle to remain autonomous while facing the complex and changeable external environment.The trajectory tracking control system with high accuracy and stability is the basic guarantee for the autonomous navigation of unmanned surface vehicle.so it is of great significance to study the trajectory tracking control method of unmanned surface vehicle.when the unmanned surface vehicle sails on the sea,it is susceptible to the external environment of wind,wave,flow.At the same time,the motor system is a special kind of nonlinear system,so the study of unmanned surface vehicle trajectory tracking control method has a great challenge.On the other hand,in the actual voyage,because it is usually difficult to measure the state vectors of the unmanned surface vehicle speed.So the traditional control method is difficult to solve the existing problems.It needs to explore new control method of the unmanned surface vehicle.In this paper,two different trajectory tracking controllers are designed based on the sliding mode control theory.Firstly,on account of the uncertainties and external disturbances in the system,the three degree of freedom mathematical model of the surface unmanned boat is established by weakening complex conditions.The mathematical model is the basis of trajectory tracking controller design and trajectory tracking simulation.Secondly,on account of the speed of unmanned surface vehicle is immeasurable,basing on the observer the trajectory tracking control is designed.A stable observer is designed by using the nonlinear transformation.In dynamic circuit,by using sliding mode control method,first and second order sliding mode surface is designed.Using exponential reaching law and combined with the estimate of the velocity vector and the kinematics of the design circuit of the virtual control law,the horizontal and vertical thrust moment of sliding mode control law are got eventually.Then,the trajectory tracking controller based on RBF neural network sliding-mode control is designed for the problem of unmanned surface vehicle trajectory tracking with external environment interference and uncertain model parameters.External environment interference is an uncertain part of model parameters.By using the RBF neural network,we can approximate the characteristics of any nonlinear function and estimate the unknown items in the unmanned surface vehicle model.At the same time,the adaptive law of neural network weight is designed to minimize the approximation error.In the kinematics circuit,by combining the expected trajectory with the actual location information,the virtual control law of kinematic loop speed is designed.It can realize the stabilization control of trajectory tracking error through the stabilization of velocity error.In the dynamic loop,by using sliding mode control method,the first order and second order sliding surface is designed.The exponential approach law is adopted to obtain the adaptive sliding mode control law and the horizontal steering torque adaptive sliding mode control law.Finally,a simulation experiment was carried out in MATLAB environment for the unmanned surface vehicle of trajectory tracking controller.The simulation results show that the above control algorithm can realize the accurate tracking control of the closed trajectory and open trajectory.So the effectiveness of the proposed algorithm is validating.