Research On Recovering Dynamic Positioning Control Of Fully Driven Autonomous Underwater Vehicle

Autonomous Underwater Vehicle(AUV)is an important tool for military and civilian applications.It plays an important role in the field of marine resource exploration and marine search and rescue.In recent years,countries around the world have paid more attention to the research and technological innovation of AUV.Due to the limited energy contained in the AUV itself,The AUV needs to be replenished through recycling,and it is too cumbersome to deploy and recycle frequently on the water surface.How to supplement the energy and data interaction for the AUV more portable has become a key technical issue for AUV applications.Aiming at the difficulties of AUV underwater autonomous recovery in complex environments,this thesis focuses on the study of dynamic positioning control methods in the recovery process,and participates in the development of an AUV underwater autonomous recovery docking system.The specific content is as follows:First,according to the technical requirements of underwater recovery and docking,combined with the self-developed " T-SEA II " AUV to design an independent recovery and docking program,which uses dynamic positioning control to improve the accuracy of recovery and docking.In addition,an AUV dynamic positioning control system model is established,and studied the force and the interference of waves and currents during the movement of AUV.Then,for the AUV dynamic positioning control during the recovery process,a non-linear model predictive control method for the AUV dynamic positioning based on the extended state observer is proposed.This method introduces the extended state observer to compensate for the model deviation and external interference of the system.The nonlinear model predictive controller is designed on the horizontal and vertical motion,and the optimal control strategy under the constraint conditions is solved through the controller.At the same time,the torque priority thrust distribution algorithm is designed to take advantage of the multi-thruster advantage of the " T-SEA II " full-drive AUV to improve water performance.The flexibility and adaptability of the downstream operation,under the condition of ocean current disturbance,respectively carry out dynamic positioning fixed-point control,fixed-depth straight-line tracking and trajectory tracking and other sets of simulation experiments.Secondly,a novel state estimation algorithm of adaptive minimum skew simplex unscented Kalman filter is designed.The algorithm adopts the minimum skew simplex unscented transform method,and at the same time uses the innovation sequence to modify the principle of adaptive estimation.The trace Kalman filter algorithm is improved to reduce the calculation amount of AUV state estimation and improve the estimation accuracy,so as to realize the AUV state estimation of the dynamic positioning control during the recovery and docking process.Finally,participated in the development of a set of AUV recovery docking system,and completed the AUV dynamic positioning and autonomous recovery docking lake test in a lake in Suzhou.The experiment mainly included fixed depth control,underwater polygon tracking control and continuous recovery docking experiment.Experiments with different initial distances and orientations verify the system's recovery and docking capabilities.The experimental results show that the AUV's dynamic positioning control is accurate and the recovery and docking success rate is high.