Adaptive Passivity-Based Pose Tracking Control of Cable-Driven Parallel Robots for Multiple Attitude Parameterizations
Sze Kwan Cheah, Alex Hayes, Ryan J. Caverly
Abstract
This article presents a pose tracking controller for a six degree-of-freedom (DOF) overconstrained cable-driven parallel robot (CDPR). The proposed control method uses an adaptive feedforward-based controller to establish a passive input–output mapping for the CDPR. This is used alongside a linear time-invariant (LTI) strictly positive real (SPR) 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 models. The results show that making use of a multiplicative computation of the pose error, such as when the quaternion or DCM is used within the control law, results in better performance compared to the use of linearized Euler-angle parameterization often used for control of CDPR.