Impedance Control of a Transfemoral Prosthesis using Continuously Varying Ankle Impedances and Multiple Equilibria
This work addresses a practical problem for lower limb prosthesis developers by providing a more credible and cost-effective alternative to expensive perturbation studies for impedance parameter estimation.
This paper tackled the discrepancy between least squares optimization and perturbation studies for estimating ankle impedance parameters in prosthetic control by extending the least squares approach to reproduce perturbation study results, successfully testing the parameters on the AMPRO II transfemoral prosthesis and applying the method to knee impedance estimation.
Impedance controllers are popularly used in the field of lower limb prostheses and exoskeleton development. Such controllers assume the joint to be a spring-damper system described by a discrete set of equilibria and impedance parameters. Said parameters are estimated via a least squares optimization that minimizes the difference between the controller's output torque and human joint torque. Other researchers have used perturbation studies to determine empirical values for ankle impedance. The resulting values vary greatly from the prior least squares estimates. While perturbation studies are more credible, they require immense investment. This paper extended the least squares approach to reproduce the results of perturbation studies. The resulting impedance parameters were successfully tested on a powered transfemoral prosthesis, AMPRO II. Further, the paper investigated the effect of multiple equilibria on the least square estimation and the performance of the impedance controller. Finally, the paper uses the proposed least squares optimization method to estimate knee impedance.