Tri-Space Operational Control of Redundant Multilink and Hybrid Cable-Driven Parallel Robots Using an Iterative-Learning based Reactive Approach

2026-07-31

AI Summary

This study addresses the challenge of high-precision trajectory tracking for redundant multi-link and hybrid cable-driven parallel robots under simultaneous constraints in actuation, joint, and task spaces—collectively referred to as the three-space constraints. To this end, a unified three-space control framework integrating reactive control (RC) and iterative learning control (ILC) is proposed. The framework enables, for the first time, a consistent modeling approach applicable to diverse redundant cable-driven architectures and introduces a novel parametrization of null-space vectors that concurrently satisfies three-space constraints and optimizes performance over repetitive tasks. Experimental validation demonstrates that the method operates in real time across multiple robot configurations, effectively preventing cable interference, joint collisions, and loss of manipulability, thereby significantly enhancing trajectory tracking accuracy and system robustness.

Abstract

Cable-Driven Parallel Robots (CDPRs) are a type of parallel mechanism in which cables are used as actuators. Due to the two levels of redundancy and numerous constraints within the CDPR actuation, joint and operational spaces (together known as the tri-space), tracking a given trajectory in the operational space while satisfying constraints in tri-space simultaneously is challenging. To the best of the authors' knowledge, there does not exist any tri-space control framework, which is robust, effective, and directly applicable to several architectures of redundantly actuated CDPRs. This paper proposes a tri-space control framework that combines Reactive Control (RC) and Iterative-Learning Control (ILC) to perform repetitive tasks in the operational space. The framework allows the tracking of operational space trajectories online with feasible cable forces, while avoiding undesirable situations such as cable-link interference, joint interference, and loss of manipulability. On the other hand, by finding an optimal parameter in the null space using a novel parameterization of a null space vector, the performance can be improved through ILC when the task is repeatedly executed. Simulation and hardware results on various Multilink Cable-Driven Robot (MCDRs) and Hybrid Cable-Driven Robots (HCDRs) show that the proposed tri-space control framework can be conveniently and effectively applied to the real-time control of different CDPRs.

Problem

• Cable-Driven Parallel Robots
• tri-space control
• redundancy
• trajectory tracking
• constraints

Innovation

• Tri-space control
• Cable-Driven Parallel Robots
• Iterative-Learning Control
• Reactive Control
• Null-space parameterization