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Dynamic model identification of the 2-Axes PAM robot arm using neural MIMO NARX model

Hồ Phạm Huy Ánh, Kyoung Kwan Ahn, Yoon Jong Il

Year
2008
Citations
8

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’s inverse dynamic model. The contact force variations and highly nonlinear coupling features of both links of the 2-axes PAM robot arm are modeled thoroughly through an Inverse Neural MIMO NARX Model-based identification process using experiment input-output training data. For the first time, the nonlinear Inverse Dynamic MIMO NARX Model scheme of the prototype 2-axes PAM robot arm has been investigated. The results show that proposed dynamic intelligent model trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy.

Keywords

Nonlinear autoregressive exogenous modelComputer scienceIdentification (biology)RobotControl theory (sociology)Robotic armMIMOArtificial neural networkArtificial intelligenceControl engineering

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