The design of impedance controllers for sloped walking with a transfemoral prosthesis is a complex control problem that generally results in numerous tuning parameters. This study proposes an easy-to-tune sloped walking control scheme. While the ankle is controlled using impedance control, the knee is controlled using a hybrid strategy of impedance control and trajectory tracking. This study derived continuous, nonlinear impedance functions for the ankle and knee joints using optimization. Principal component analysis of the impedance functions revealed trends that can be used to design impedance controllers for any given slope angle. Said trends were further used to establish a tuning regime which was subsequently tested on a transfemoral prosthesis in an emulator study. The generated gait kinematics and kinetics were found to follow the trends of healthy sloped walking data.

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. These 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 ankle impedance parameters were successfully tested on a powered transfemoral prosthesis, AMPRO II. Further, the paper investigated the effect of multiple equilibria on the least squares estimation and the performance of the impedance controller. Finally, the paper uses the proposed least squares optimization method to estimate knee impedance.