This paper investigates a novel forward adaptive neural MIMO NARX model which is applied for modeling and identifying the forward kinematics of the industrial 5-DOF robot arm system. The nonlinear features of the forward kinematics of the industrial 5-DOF robot arm drive are thoroughly modeled based on the adaptive 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 industrial 5-DOF robot arm. The results show that the proposed adaptive neural NARX model trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy. © Springer-Verlag Berlin Heidelberg 2014.
CITATION STYLE
Anh, H. P. H., & Nam, N. T. (2014). Adaptive line trajectory identification of industrial 5-DOF robot arm using neural MIMO NARX model. In Lecture Notes in Electrical Engineering (Vol. 282 LNEE, pp. 605–615). Springer Verlag. https://doi.org/10.1007/978-3-642-41968-3_60
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