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Adaptive Control of a Robotic Arm Using Neural Networks Based Approach
mahdi vaezi, Mohammad Ali Nekouie, Farid Najafi
Pages - 87 - 99     |    Revised - 31-01-2011     |    Published - 08-02-2011
Volume - 1   Issue - 5    |    Publication Date - January / February 2011  Table of Contents
nonlinear multivariable system, neural networks, robotic arm, NARMA-L2 controller, speed trajectory
A new neural networks and time series prediction based method has been discussed to control the complex nonlinear multi variable robotic arm motion system in 3d environment without engaging the complicated and voluminous dynamic equations of robotic arms in controller design stage, the proposed method gives such compatibility to the manipulator that it could have significant changes in its dynamic properties, like getting mechanical loads, without need to change designs of the controller.
CITED BY (3)  
1 Salih, D. M., Noor, S. B. M., Hamiruce Merhaban, M., & Kamil, R. M. (2015). Wavelet Network: Online Sequential Extreme Learning Machine for Nonlinear Dynamic Systems Identification. Advances in Artificial Intelligence, 2015.
2 Zacharie, M. (2012). Advanced logistic belief neural network algorithm for robot arm control. Journal of Computer Science, 8(6), 965.
3 Gupta, A., Vig, L., & Noelle, D. C. (2011). A cognitive model for generalization during sequential learning. Journal of Robotics, 2011.
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Mr. mahdi vaezi
science and research branch of islamic azad university - Iran
Dr. Mohammad Ali Nekouie
KNT technical university - Iran
Dr. Farid Najafi
KNT technical university - Iran