Abstract
In this paper, a novel Inverse Dynamic MIMO NARX model is used for modeling and identifying simultaneously both of joints of the prototype 2-axes PAM robot arm. The contact force variations and highly nonlinear coupling features of both links of the 2-axes PAM system are modeled thoroughly through an Inverse Neural MIMO NARX Model-based identification process using experiment input-output training data. For the first time, the dynamic Inverse neural MIMO NARX Model of the 2-axes PAM robot arm has been investigated. The results show that the neural Inverse Dynamic MIMO NARX Model trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy.
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