Abstract
An adaptive neural network control design for robot manipulators in task space coordinates is provided in this paper. This controller design and a direct adaptive control strategy (passivity-based controller) are simulated for the same trajectory, considering the presence of the friction torques and the influence of payload. Performances are evaluated according to behavior of position tracking, and to trajectory tracking accuracy. The adaptive neural network controller is developed based on a neural network modeling technique which neither requires the evaluation of inverse dynamical model nor the time-consuming training process, and does not require the inverse of the Jacobian matrix.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
