Research On Path Planning And Trajectory Tracking Control Of Underdriven Unmanned Surface Vehicles In Shallow Waters

With the rapid development of economy and control technology,the demand for unmanned surface vehicles in military field and civil field is increasing.Because of their small size,high flexibility and various functions,they are suitable for inland waterways and offshore scenarios to perform dangerous and boring tasks.In this paper,we design a global+local path planning strategy that can drive in complex environments by taking inland-class underactuated unmanned surface vehicles driving in shallow waters with uncertain obstacles for multi-mission target point cruising as the core of the research.Meanwhile,the underactuated unmanned surface vehicles is a strongly coupled,multi-input,multi-output nonlinear system.Compared to large unmanned surface vehicles,small unmanned surface vehicles are more vulnerable to the external environment.Trajectory tracking as an important part of its motion control,due to the complex and variable water surface disturbance,it is difficult to design a single control strategy to meet the requirements of strong robustness and high adaptivity,and cannot achieve the expected set control performance standards.Therefore,this paper investigates the global + local path planning and trajectory tracking control strategies for underactuated unmanned surface vehicles.The main research contents of this paper are as follows:(1)Combined with the motion characteristics of the unmanned surface vehicles,the kinematic model and dynamics model of the three-degree-of-freedom underactuated unmanned surface vehicles are established,and the established mathematical model and the parameters of the unmanned surface vehicles are simulated and verified.(2)The RRT*+DWA algorithm is used to complete the path planning for the proposed model and the mission requirements of the unmanned surface vehicles multitarget cruise.The global path planning is based on the map of known obstacles,and the global path is finally obtained by solving the access order of mission target points(Traveling Salesman Problem)through fusion genetic algorithm seeking optimization.When navigating in the global path,the DWA algorithm is triggered to do dynamic local obstacle avoidance when the unknown obstacles reach within the safe distance of the unmanned surface vehicles,and returns to the global path to continue driving after the local obstacle avoidance is completed.The path planning algorithm can guarantee that the unmanned surface vehicles can complete its work safely and efficiently in the complex shallow water environment.(3)To solve the problem that the unmanned surface vehicles is vulnerable to external environmental disturbances,the backstepping sliding mode control is designed.The parameter uncertainty of the unmanned surface vehicles model affects the control of the unmanned surface vehicles.A finite-time observer is used to predict the model uncertainty and environmental disturbances,while an observer is used to estimate the velocity state value online to reduce the dependence on the velocity sensor.The LOS line-of-sight governing law is introduced in the controller design link to reduce the jitter of the controller input and improve the convergence speed and tracking accuracy.The first-order filter signal is used instead of the virtual control law to avoid differential explosion from the derivation of the virtual control law.The feasibility and practicality of the algorithm are verified by conducting Lyapunov stability analysis of the observer and controller,and simulation experiments of the control algorithm.(4)To further improve the dynamic performance and steady-state performance of the trajectory tracking control error,a pre-defined performance control strategy is designed.By designing the disturbance observer,not only the accurate estimation of environmental disturbance is achieved,but also the position and velocity estimates of the ship are provided,which reduces the dependence of the ship on high-precision velocity sensors and high-precision inertial navigation,reduces the application cost,and improves the control accuracy of the trajectory tracking system.In the controller design stage,the performance function is introduced and error conversion is performed to design the controller by combining the backstepping method with Lyapunov stability theory,so that the predefined performance function can dynamically constrain the tracking error of the unmanned surface vehicles in dynamic performance and steadystate performance to meet the desired performance criteria.The feasibility and superiority of the algorithm is illustrated by stability analysis and comparative simulation verification with the backstepping sliding mode control algorithm.