Adaptive Passivity-Based Pose Tracking Control of Cable-Driven Parallel Robots for Multiple Attitude Parameterizations

The proposed control method uses an adaptive feedforward-based controller to establish a passive input-output mapping for the CDPR that is used alongside a linear time-invariant strictly positive real feedback controller to guarantee robust closed-loop input-output stability and asymptotic pose trajectory tracking via the passivity theorem. A novelty of the proposed controller is its formulation for use with a range of payload attitude parameterizations, including any unconstrained attitude parameterization, the quaternion, or the direction cosine matrix (DCM). The performance and robustness of the proposed controller is demonstrated through numerical simulations of a CDPR with rigid and flexible cables. The results demonstrate the importance of carefully defining the CDPR’s pose error, which is performed in multiplicative fashion when using the quaternion and DCM, and in a specific additive fashion when using unconstrained attitude parameters (e.g., an Euler-angle sequence).

💡 Research Summary

The paper addresses the challenging problem of pose (position and orientation) tracking for over‑constrained cable‑driven parallel robots (CDPRs), which feature more cables than degrees of freedom and consequently exhibit redundancy, force‑distribution complexity, and significant model uncertainty (e.g., payload inertia variations, flexible‑cable dynamics). The authors propose a unified control architecture that combines an adaptive feed‑forward component with a linear time‑invariant strictly positive real (SPR) feedback controller, and they prove closed‑loop stability and asymptotic tracking by invoking the passivity theorem.

Key ingredients of the control design

1. Dynamic model – The robot dynamics are expressed in task space as (M(\rho)\dot\nu + D(\rho,\nu)\nu + g(\rho) = \Pi^T(\rho)\tau), where (\rho =