Research On Control System Development And Dynamic Positioning Method Of Underwater Operation ROV

Currently,remotely operated vehicle(ROV)has advantages such as safety,economics and high efficiency that is widely utilized to underwater structure survey,submarine cable repair,exploitation of marine resources.Due to the increasing difficulty of ROV's operation task,its operation accuracy and reliability cannot be guaranteed.Based on high-tech ship collaborative innovation center in jiangsu province in 2017 research projects,to participate in a testing job type modular ROV prototype was developed,and the design of the ROV control system,the six degree of freedom model is established,the near surface model is simplified,the space gesture description,inertial sensor data fusion,several key technical problems and dynamic positioning controller design is studied.According to the development requirements of the project,participate in the overall design of ROV,and complete the development of ROV control system.Specifically,it includes the hardware design,software development,functional test and optimization improvement of the surface control console,underwater main control board,slave control board,inertial data processing board,manipulator control board and other modules.On the ROV motion model of each degree of freedom coupling between serious and model parameter uncertainty problems,based on Newton's laws of motion and the law of moment of momentum,combining with the working conditions of the ROV near surface,the characteristics of movement and force analysis process,the introduction of the external environment disturbance model,and the ROV decoupling simplified six degrees of freedom movement model,for the data fusion algorithm and dynamic positioning controller design to lay the foundation.Aiming at the problems of poor accuracy and external interference in the attitude solution of ROV with a single inertial sensor.Based on multi-sensor fusion system framework,combining inertial sensor measurement model,the multiple inertial sensor data fusion algorithm of calculating the ROV optimal attitude research,and implements the three different algorithms of attitude algorithm process,by testing the inertia of a data processing board compares the three algorithms on the attitude algorithm accuracy and magnetic interference.The principle of sliding mode control and the method of RBF neural network approximating unknown function are studied,and an adaptive sliding mode controller of RBF neural network is designed.The stability and convergence of the proposed algorithmare proved and compared with the simulation results of the traditional adaptive sliding mode control method.Simulation results show that the tracking effect of ROV is well in the wave-disturbed environment.Finally,the function test and joint adjustment test of the developed hardware driver boards and operating tools are carried out,and the experiment proves that the ROV attitude data calculated by the data fusion algorithm is of high reliability and can recover to the previous attitude after magnetic interference.ROV basic motion control and underwater target observation functions were completed in the pool to achieve the expected standard.