Effective control strategies for robotic manipulators require on-line computation of the robot dynamic model in real-time. However, the complexity of robot dynamic model makes this difficult to achieve in practice. Neural networks are an attractive alternative for identification and control of robotic manipulators, because of their ability to learn and approximate functions. This paper presents the development of an adaptive Multilayer Neural Network (MNN) as a feedforward controller for a robotic manipulator. The MNN is trained to identify the unknown nonlinear plant (inverse dynamics of a robotic manipulator) using a modified back-propagation technique. A PD controller is used in the feedback loop to guarantee global asymptotic stability. Also, the output of the PD controller is used as a learning signal for the on-line learning to adjust the weights of the MNN to capture any parameters variation and/or disturbances. The controller architecture developed has been simulated and its effect on the trajectory tracking performance of a manipulator has been evaluated and compared to the conventional adaptive controller.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Adaptive neural network for identification and tracking control of a robotic manipulator


    Contributors:
    Ahmed, R.S. (author) / Rattan, K.S. (author) / Abdallah, O.H. (author)


    Publication date :

    1995-01-01


    Size :

    750585 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Adaptive Neural Network for Identification and Tracking Control of a Robotic Manipulator

    Ahmed, R. S. / Rattan, K. S. / Abdallah, O. H. et al. | British Library Conference Proceedings | 1995


    Robust Adaptive Neural-Fuzzy Network Tracking Control for Robot Manipulator

    Ngo, ThanhQuyen / Wang, YaoNan / Mai, T. Long et al. | BASE | 2014

    Free access

    Robust Adaptive Tracking Control of Manipulator Arms with Fuzzy Neural Networks

    Fouzia, M. / Khenfer, N. / Boukezzoula, N. E. | BASE | 2020

    Free access

    Robust Adaptive Trajectory Tracking Sliding Mode Control for Industrial Robot Manipulator using Fuzzy Neural Network

    Xuan, Quynh Nguyen / Cong, Cuong Nguyen / Ba, Nghien Nguyen | BASE | 2024

    Free access

    Improving Trajectory Tracking Performance of Robotic Manipulator Using Neural Online Torque Compensator

    Al Ashi, Mahmoud M. / Abu Hadrous, Iyad / Elaydi, Hatem | BASE | 2016

    Free access