Tension-based Dynamic Control for Rope-Driven Robots under Edge Collisions

Abstract

This paper presents a tension-based dynamic control framework with torque-level tension tracking for a rope-driven ascending robot (RDAR), which differs from the position-based control schemes used in previous RDAR studies. The robot operates in unstructured environments where rope–edge collisions introduce significant disturbances such as anisotropic friction and tension loss. To address these effects, a hierarchical control architecture is developed that integrates a sliding-mode controller with adaptive gain (SMC-AG) and a disturbance observer (DOB). The high-level controller generates tension references using real-time tension feedback to reject collision-induced disturbances, while the low-level controller directly tracks these tensions in the motor-torque domain via PID control with model-based feedforward compensation derived from ascender dynamics. Lyapunov-based analysis guarantees closed-loop stability. A compact rope–edge experiment characterizes collision-induced friction and supports the disturbance modeling assumptions. Real-time tension regulation further mitigates rope hysteresis and improves responsiveness. Experimental results across various trajectories and speeds show that the proposed controller reduces the RMS tracking error by up to 80% and the peak error by 20% compared to conventional position-based PID with feedforward compensation, demonstrating strong robustness against edge interactions.