Abstract
In this paper, the application of an impedance control scheme to drive a robot with a desired force profile in the presence of non-rigid environments is considered. However, for the usual impedance based control schemes, fine control of the contact force especially for non-rigid environments is difficult to obtain. Moreover, unmodeled robot model effects and environment uncertainties, can seriously affect the force tracking performance. In this paper, the nonlinear uncertainties in a model-based impedance controller are compensated by an on-line neural network compensation scheme. Further, a predictive algorithm is designed to compute the optimized virtual trajectory for the impedance controller in order to precisely track the desired force profile. The performance of the proposed control scheme is illustrated by simulation for a three degree-of-freedom PUMA 560 robot, which end-effector is forced to move along a surface located on the vertical plane. Simulation results reveal an accurate force tracking performance for the proposed force control scheme, in the presence of non-rigid environments.
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.
