Six Degree Of Freedom Stable Platform Based On Ship Motion Prediction

With the development of domestic economy,China has formed a marine economic system of many industries,and the duration of offshore operations is increasing.Due to the influence of the marine environment,the ship will have a motion of six degrees of freedom.In order to facilitate the operation of offshore personnel,the marine stable platform can compensate the movement of the ship and provide a stable environment for the staff and working equipment.At present,the mainstream marine stable platform is the series platform.The series platform has simple structure but small stiffness,which can not meet the requirements of high response and large load.The six degree of freedom parallel stable platform can compensate the six degree of freedom movement of the ship,and the parallel stable platform has fast response speed,strong stiffness and high bearing capacity,which can cope with large load.This paper mainly studies the Stewart Parallel stable platform.This paper introduces the composition and working principle of the six degree of freedom stable platform,defines the coordinate system of the stable platform,analyzes the kinematics of the parallel stable platform,establishes the inverse and forward kinematics models,and then carries out the dynamic analysis of the six degree of freedom stable platform.In this paper,the ship motion characteristics and prediction algorithm are analyzed.The parallel six degree of freedom stabilized platform has response lag,which is one of the factors affecting the stability accuracy.Therefore,it is necessary to predict the motion of the ship to compensate for the response lag of the system.This paper first analyzes the wave motion,then analyzes the ship motion characteristics,and finally analyzes the non periodic signals generated by the ship motion.In this paper,two schemes are used for ship motion prediction.Firstly,the parameter model method based on AR model is used to predict the ship motion,and the recursive correlation moment algorithm is used to estimate the model parameters,and then the information criterion method is used to determine the order of the model;Secondly,the RBF neural network method is used to predict the ship motion.The Gaussian function is used as the basis function to calculate the connection weight of the neural network,and then the prediction value of the ship motion is obtained;Finally,this paper uses the ship motion signal to verify the two methods.The calculation results show that the two methods can better fit the ship motion data,and the RBF neural network method has higher fitting accuracy and lower relative error rate.In this paper,the prediction data of the two methods are input into the stable platform model.Through comparison,it is found that the two methods can improve the motion accuracy of the parallel stable platform and effectively reduce the motion amplitude of the upper platform.The RBF neural network method has higher prediction accuracy in the two methods.Finally,this paper verifies the feasibility of the ship prediction algorithm by simulation.