Abstract
In this paper, a novel inverse adaptive neural MIMO NARX model is used for modeling and identifying the inverse kinematics of the humanoid robot 3-DOF arm system. The nonlinear features of the inverse kinematics of the industrial robot arm drive are thoroughly modeled based on the inverse adaptive neural NARX model-based identification process using experimental input-output training data. This paper proposes the novel use of a back propagation (BP) algorithm to generate the inverse neural MIMO NARX (INMN) model for the inverse kinematics of the humanoid robot 3-DOF arm. The results show that the proposed adaptive neural NARX model trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have