Dynamic Model Identification of PAM-Based Rehabilitation Robot Using Neural MIMO NARX Model

Abstract

In this paper, a novel Forward Dynamic MIMO Neural NARX model is used for simultaneously modeling and identifying both joints of the 2-axes PAM robot arm’s forward dynamic model. The contact force variation and highly nonlinear cross effect of both links of the 2-axes PAM robot arm are modeled thoroughly through a Forward Neural MIMO NARX Model-based identification process using experiment input-output training data. Consequently the proposed Forward Dynamic Neural MIMO NARX model scheme of the nonlinear 2-axes PAM robot arm has been investigated. The results show that the novel Forward Dynamic Neural MIMO NARX Model trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy.