Abstract
In this paper a neural-net (NN) controller for tracking control of a manipulator is used. A manipulator is a nonlinear object which usually has unknown and changeable parameters. Dynamics equations of a rigid manipulator are presented. A NN controller is used for compensating manipulator's nonlinearities. The controller is realized in a form of a linear NN in the weights. The NN is learned by using backpropagation tuning. The presented control law and tuning algorithm are derived from the Lyapunov direct method. In this paper results of simulation and experiment are presented.
Sign-in/Register to access full text options 
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.
