Research On Track Control Of Underwater Manipulator For Capture Purpose

With the development and progress of human science and technology,people are exploring more and more unknown fields.Occupying the largest area on the earth and with the most abundant resources,the ocean has gradually become an important exploration field for human beings,and a large number of underwater equipment have been developed for deep-water exploration,refloatation,underwater maintenance and other operations.It is becoming an important way to carry out underwater operation by using underwater platform to carry a small vehicle.Based on the engineering problem that the underwater robot arm tracks the small scale vehicle in its working space for capture and recover,energy supplement and data exchange,this paper studies the trajectory tracking control problem of the underwater manipulator on the unmanned underwater vehicle(UUV).In this paper,the kinematics of the manipulator model is analyzed firstly.The Monte Carlo method is used to analyze the motion space of the end of the manipulator,and the Lagrange method is used to model the dynamics of the manipulator.Combined with the analysis of the force of the underwater manipulator,the complete dynamics model of the underwater manipulator is obtained.A non-singular fast terminal sliding mode control method based on fuzzy selfadaptation is designed according to the established model of the underwater manipulator.On the basis of traditional sliding mode control,the terminal sliding mode control is adopted to solve the problem that the system cannot converge to the sliding mode surface in finite time.Considering the singularity problem of the terminal sliding mode control,a nonsingular terminal sliding mode control is proposed,and the convergence speed and precision of the system are improved by adding fast term and integral term.Finally,a fuzzy controller is used to approximate the switching term of the sliding mode control,so that chattering can be reduced.The simulation results show that when the control system adopts the fuzzy adaptive non-singular fast terminal sliding mode control,the convergence speed of the system is faster,the control precision is higher,and the chattering of the control input is reduced effectively.Considering the unknowability of the underwater environment and the uncertainty of the system parameters of the manipulator,the terminal sliding mode control based on neural network block approximation is proposed.The basic principle of neural network is analyzed,the property of the neural network system being on any continuous nonlinear function approximation is used,the coefficient matrix of the dynamic model and the uncertain part have been approximated.This method not only can effectively control to the system but can also reduce the chattering phenomenon of sliding mode control,and finally the fast terminal sliding mode control is used to speed up the convergence speed and improve the system robustness.The simulation results show that the fast terminal sliding mode control method based on neural network block approximation can achieve effective tracking of the given trajectory of the robot arm system with uncertainties.In order to better verify the tracking control method of underwater manipulator,a simulation test platform in air has been designed and built.A six-degree-of-freedom platform is used to simulate the underwater moving platform,on which a manipulator is mounted.A small scale mimic vehicle is mounted to another six-degree-of-freedom platform.Through the motion of two six-degree-of-freedom platforms,the underwater motion disturbance in the tracking process has been simulated.The hardware and software of the mechanical system and control system of the test platform have been designed and realized,so as to complete the construction of the whole simulation test system,which laid a foundation for the development of the test.