Novel Adaptive Forward Neural MIMO NARX Model Application for Modelling of Biped Robot's Arm Kinematics

Abstract

In this paper, a novel forward adaptive neural MIMO NARX model is used for modelling and identifying the forward kinematics of the biped robot's 3-DOF arm system. The nonlinear features of the forward kinematics of the industrial robot arm drive are thoroughly modelled based on the forward 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 forward neural MIMO NARX (FNMN) model for the forward kinematics of the biped robot's 3-DOF arm system. The results show that the proposed adaptive neural NARX model trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy.