Research On The Methods For Motion Planning And Path Tracking Motion Control Of AUV

Autonomous Underwater Vehicle(AUV)is the focus of ocean research from view of experts and scholars all over the world.It is a main direction of current AUV research to improve the intelligent level.Therefore,the problems of AUV motion planning and AUV motion control are focused in this paper,which have important theoretical significance and practical value in strengthening autonomy and safety of AUV and improving the capability of diversity mission fulfillment.Firstly,AUV Beaver is regarded as the research subject in this paper,and its dynamics model and kinematics model are studied respectively,which are the foundation for subsequent research on motion planning.In general,numerical processing is not convenient for motion planning due to coupling relationship between different degrees of freedom and nonlinear terms in the dynamic model.Therefore,the simplified dynamics model with single degree of freedom is adopted for motion planning in this paper.Simulation results of AUV Beaver maneuvering in horizontal plane verify the accuracy of dynamics model with single degree of freedom.In addition,environmental disturbance force acting on the dynamics model is also analyzed.Secondly,the motion planning algorithm based on gradient descent is proposed in this paper.Effectiveness of gradient descent algorithm is verified through simulations in the environment with typical obstacles.Simulation results show that the path leading to goal point with obstacle avoiding can be obtained by applying the motion planning algorithm when AUV encounters intensive obstacles.The adaptive strategy for control input sampling is also proposed in this paper in order to solve the problem of falling into local minimum when AUV encounters U shape obstacle.AUV can escape from local minimum through the adaptive strategy,which self-expands the range of control input sampling when AUV approaches local minimum.The defect of falling into local minimum is overcome obviously by applying this method when AUV encounters U shape obstacle.Thirdly,the motion planning algorithm based on SBMPC(Sampling Based Model Predictive Control)is proposed by introducing the idea of model predictive control in this paper.Input sampling is directly made in control variable space,and sampling data is substituted into the predictive model of AUV motion.Then surge velocity and yaw angular rate in next sampling time are obtained through calculations.If predictive states are evaluated according to the performance index previously defined,optimal prediction of AUV states in next sampling can be used to realize motion planning optimization.Effects of three sampling methods(viz.uniform sampling,Halton sampling and CVT sampling)on motion planning performance are also compared in simulations of SBMPC algorithm in order to make input sampling reflect the feature of control variable completely and accurately.Statistical analysis demonstrates that CVT sampling points has the most uniform coverage in two-dimensional plane when amount of sampling points is the same for three methods.Simulation results show that it is effective and feasible to plan a route for AUV by using CVT sampling and rolling optimization of MPC(Model Predictive Control).Finally,a new controller used for AUV path tracking is designed in this paper.In order to solve the problem relating to nonlinear dynamic model of AUV(Autonomous Underwater Vehicle),feedback linearization method is firstly adopted to transform the nonlinear dynamic model into an equivalent pseudo-linear dynamic model in horizontal coordinates.Then considering wave disturbance effect,mixed-sensitivity method of H-infinity robust control is applied to design state-feedback controller for this equivalent dynamic model.Finally control law of pseudo-linear dynamic model is transformed into state(surge velocity and yaw angular rate)tracking control law of nonlinear dynamic model through inverse coordinate transformation.Simulation indicates that AUV path tracking is successfully implemented with this proposed method,and the influence of parameter variation in AUV dynamic model on its tracking performance is reduced by H-infinity controller.