Load-independent Metrics for Benchmarking Force Controllers

TL;DR

This paper introduces load-independent metrics for benchmarking torque controllers, combining passivity and small-gain theory to evaluate stability regardless of load variations, supported by experimental validation.

Contribution

It presents a novel modeling approach and new quantitative metrics, including the Passivity Index Interval, for load-independent assessment of torque-controlled systems.

Findings

Proposed metrics effectively characterize stability across different loads.

Experimental results validate the usefulness of the new metrics.

Metrics complement traditional control performance indicators.

Abstract

Torque-controlled actuators are critical components in mechatronic systems that closely interact with their environment, such as legged robots, collaborative manipulators, and exoskeletons. The performance and stability of these actuators depend not only on controller design and system dynamics but also significantly on load characteristics, which may include interactions with humans or unstructured environments. This load dependence highlights the need for frameworks that properly assess and compare torque controllers independent of specific loading conditions. In this short paper, we concisely present a modeling approach that captures the impact of load on the closed-loop dynamics of torque-controlled systems. Based on this model, we propose new methods and quantitative metrics, including the Passivity Index Interval, which blends passivity and small-gain theory to offer a less conservative measure of coupled stability than passivity alone. These metrics can be used alongside traditional control performance indicators, such as settling time and bandwidth, to provide a more comprehensive characterization of torque-controlled systems. We demonstrate the application of the proposed metrics through experimental comparisons of linear actuator force controllers.