This study aims to efficiently establish an accurate static stiffness model for closed-loop parallel manipulators while ensuring practical identification efficiency.
An equivalent joint stiffness identification method is proposed in this paper. This method incorporates the contact interface stiffness between internal components within each joint during the stiffness modeling. The entire system is then equivalently modeled as a hypothetical robotic system containing actuated and constrained joints, whose stiffness parameters are parameterized using high-order polynomial functions. Following this, an indirect loading experiment scheme and an identification-pose optimization strategy are proposed for stiffness parameter identification to improve identification efficiency and reduce the reliance on traditional multidimensional loading and dense multipose experiments.
The proposed method enables stiffness parameter identification with a reduced experimental burden while maintaining modeling accuracy. Experimental studies on a parallel manipulator at independent validation poses demonstrate that the identified stiffness model provides reliable stiffness prediction.
This study integrates internal joint contact interface stiffness into a system-level equivalent stiffness identification framework and combines unidirectional loading with pose optimization to improve identification efficiency for closed-loop parallel mechanisms.
