Research On ROV Dynamic Positioning Control Of Underwater Operating Vehicle

The reserves of oil and natural gas in China's adjacent waters are about 4 to 5 billion tons.In order to better detect and develop marine resources,it is necessary to strengthen the research and development of marine engineering detection devices and mining equipment.Offshore oil and gas development from exploration,drilling,and mining to crude oil transportation requires extensive operations such as installation,maintenance,and overhaul of underwater equipment.Underwater operations are complex,with high technical and precision requirements.Remote Operated Vehicle(ROV)is one of the most important equipments for deep-sea auxiliary oil and gas extraction.ROV can undertake some heavy-duty tasks,such as installation,inspection and maintenance of submarine pipelines,and auxiliary oil recovery.Installation of equipment,etc.Firstly,the design and development of the underwater monitoring system for ROV is completed.The water surface monitoring system consists of a control panel,an industrial computer,a hard disk recorder,and a display screen.The underwater robot control command is sent to the industrial computer through serial communication through the STM32 acquisition control panel information.The industrial computer develops the human-computer interaction interface with Qt as the development platform,controls the movement of the underwater robot through network communication and displays the motion posture of the underwater robot,the state of the propeller and the data storage,video display and other functions.Then,the state estimation method for dynamic positioning of ROV is studied.The directional dynamic model and the vertical dynamics model of the ROV are established.The state estimation of Particle Filter(PF),Extended Kalman Filter(EKF),Unscented Kalman Filter(UKF)and particle filter fusion extended kalman filter estimation algorithm(EKF/PF)in ROV dynamic positioning is studied.In this paper,a new method based on particle filter fusion unscented Kalman filter estimation algorithm(UKF/PF)for ROV dynamic localization state estimation is proposed.The simulation results show the superiority of particle filter fusion unscented Kalman filter algorithm.Secondly,the control method of dynamic positioning of ROV is studied.A novel dynamic model control method based on exponential approach law for discrete sliding mode control is designed by using the dynamic model of ROV.The simulation results show that the superiority of discrete sliding mode control algorithm based on exponential approach law.Finally,the debugging of the serial communication and network communication of the underwater surveillance system,the debugging of the STM32 data acquisition board,and the underwater navigation and depth determination experiments of the underwater working robot are carried out.