Passivity-Based vs Momentum-Residual-Based External Disturbance Compensation for Closed Loop Torque Control: A Comparative Study

In torque-controlled robotic systems, external dis- turbances, whether from physical interactions or unmodeled dynamics, can significantly affect stability and performance. This paper investigates two different approaches for external disturbance compensation within closed-loop torque control frameworks: passivity-based compensation and residual-based compensation. The former leverages discrepancies between predicted and measured joint torques to estimate external forces, enabling fast reactive control. The latter relies on passivity theory to guarantee stability by shaping the system’s energy exchange, making it robust to modeling uncertainties and sensor noise. We present the control formulations of both methods and evaluate them through experimental benchmarks in robotic tasks requiring compliant interaction. The theoretical and experimental results highlight the distinct strengths and limitations of each strategy in terms of responsiveness, stability, robustness, offering guidelines for selecting an appropriate disturbance compensation method depending on the application scenario.