Research On Trajectory Tracking Control Of Underactuated Surface Vehicles

Underactuated surface vehicle is a nonlinear system with multiple input and multiple output,strong coupling and nonholonomic system.Trajectory tracking is an important part of underactuated surface vehicle motion control.If only a single control strategy is designed,it is difficult to meet the control requirements of strong robustness and high adaptability.In the motion control of underactuated surface vehicle,there is no lateral propulsion equipment,so it has higher attention and more challenges than full-actuated vessels.Based on this,this paper takes the 3-DOF underactuated surface vehicle as the research object,and combing sliding mode variable structure theory and neural network theory to study its trajectory tracking control problem.The main idea of this paper include:(1)Model uncertain sliding mode control for trajectory tracking of underactuated surface vehicle.Aiming at the trajectory tracking control problem of USV with uncertain model parameters,a robust finite-time convergence control method based on sliding mode surface was proposed.Through the control design of the kinematics and the dynamics loop,the control state of the system moves to sliding mode and remains stable in a limited time and reduce chattering.Finally,Lyapunov stability theorem and simulation experiments are used to illustrate the effectiveness of the control method.⑵ Predefined performance trajectory tracking output feedback control of input limited underactuated surface vehicle.With the condition of control input saturation and error constraints predefined performance,the performance function limit the position tracking error and heading angle tracking error.Then use the RBF neural network to estimate the uncertain part of the unknown model and environmental disturbances,and observer is adopted to estimate speed states value online,reduce the dependence on the speed information.Through the stability analysis and simulation of the underactuated surface vehicle,the practicality and feasibility of this algorithm are proved.⑶ Trajectory tracking control of underactuated surface vehicle based on event-triggered mechanism and self-structuring neural network.In view of the unknown parameters of the underactuated surface vessel model,the self-structuring neural network can be adjusted to estimate the unknown dynamic parts and external disturbances.And adjust the number of neurons in the neural network online,so as to solve the problem of the balance between the computation and the control performance caused by the large number of neurons.The event-triggered mechanism is used to effectively solve the problem of limited communication bandwidth,to improve the efficiency of communication.The theoretical analysis and numerical simulation show that the method can effectively reduce the computation and communication bandwidth while ensuring the control performance,which makes the control strategy more effective in engineering practice.At last,summarize the research on this articles,and the future research directions,such as considering more accurate ship model and trajectory tracking control under the condition of collision avoidance are prospected.