The Forward Kinematics of the Stewart Platform Based on WOA-Elman
In order to efficiently and accurately solve the Stewart platform's forward solution problem,the whale algorithm is used to optimize the Elman neural network model in this study. The kinematic model of six linkage lengths and platform pose of Stewart platform is analyzed in detail,and the experimental data set is created by inverse solution of platform pose data. As for the Elman neural network model,whale optimization algorithm was introduced to optimize the model to improve the computational performance and accuracy,and WOA-Elman model was established to solve the positive solution of Stewart platform. The model is evaluated by detailed simulation analysis,and the validity of the model is verified by experiments. The results show that the Elman neural network model optimized by whale algorithm performs well in the forward solution of Stewart platform. The model shows excellent nonlinear fitting ability and high computational accuracy,which can quickly and accurately solve the position-attitude problem of Stewart platform. The research results provide a high-precision method for the Stewart platform position-attitude problem.
Stewart platformforward kinematicsElman neural networkoptimizationWOA-Elman model
万方数据
维普
