Research On Design And Motion Control Method Of Underwater Electric Manipulator

Currently,underwater manipulators are carried on underwater vehicles for the exploitation of underwater mineral resources and marine living resources.Since the motion system of the manipulators is inherently nonlinear and strongly coupled,the hydrodynamic interference and noise of the complex underwater environment are more likely to affect the motion control system of the manipulators.It's hard to build the control model,using traditional control method can't reach the best effect.Therefore,it is an important research direction to study a control method with higher accuracy,better stability and more effective control for underwater manipulators.Aiming at the above control difficulties,taking the designed underwater electric manipulator as a model,a control method based on fuzzy RBF(radial basis function)neural network is proposed to further improve the motion control performance of the underwater manipulator.The main contents of this paper are as follows:Firstly,an underwater electric manipulator is design in this paper.The overall design of the manipulator is based on the established parameter criterion,including the degree of freedom,the whole configuration,body material and driving mode selection.Some key parts of the manipulator are finite element analysis to verify the reliability of its design strength.Secondly,the kinematics modeling of the manipulator is established.The coordinate system of each joint of the manipulator is established by using the D-H notation to obtain the forward kinematics equation,and the inverse kinematics modeling is established by the numerical iteration method.The workspace of the manipulator is analyzed based on the Monte Carlo method,and the workspace of the manipulator is obtained in the Matlab software simulation.Thirdly,the dynamic modeling of the manipulator is analyzed.The dynamic model of the manipulator is established by the Newton-Euler method.After the original model is simplified adopting the Morison equation,the additional mass torque,water resistance torque and the buoyancy is obtained.The complete hydrodynamic equation of the manipulator is ultimately obtained.Finally,taking the previously obtained hydrodynamic equation as the control model of the manipulator motion control,a control method based on fuzzy RBF neural network is proposed.By using the method,the uncertainties including hydrodynamics in the dynamic equation of the underwater manipulator are identified overall and fitted.With the advantages of heuristic search of fuzzy system and high reasoning speed of RBF neural network,the control performance of underwater manipulator system had better precision and adaptability.In the aspect of analyzing system stability,considering the hydrodynamic term in the dynamic model,the stability of the underwater manipulator system containing hydrodynamic terms was proved by using Lyapunov stability theory.The control model is analyzed by joint simulation of Matlab and Simulink software.Comparing with the conventional RBF neural network control method,the results confirm that the proposed control method has high precision and effectiveness,it provides a higher precision,more effective control method for the underwater manipulator.