Human-robot Collaboration of Parallel Robots Based on Fractional Admittance and Inverse Dynamic Robust Control

The traditional tandem robots are of limited carrying capacity and low accuracy, and the closed-loop structure of parallel robots increases the difficulty in solving dynamics and has a slow response speed. Both structures can't meet the requirements of human-robot collaboration. This paper proposes a fractional-order admittance control algorithm to address these issues to improve response performance while enabling human-robot collaboration. An inverse dynamics robust control algorithm is also designed to ensure robustness against unknown interaction forces. The proposed control algorithm is applied to a classical Stewart parallel platform, and its response and tracking performance are evaluated through experiments. The results show that the described method resulted in an average 51.16% increase in the response speed of the Stewart parallel platform to unknown interaction forces in the Z-axis translational degree of freedom, where the loading task is heaviest, as well as an average reduction in the peak tracking error of 50.83%.