Model-Based Adaptive Control of Transfemoral Prostheses: Theory, Simulation, and Experiments

Abstract

This paper presents and experimentally implements three different adaptive and robust adaptive controllers as the first steps toward using model-based controllers for transfemoral prostheses. The goal of this paper is to translate these control methods to the robotic domain, from bipedal robotic walking to prosthesis walking, including a rigorous stability analysis. The human/prosthesis system is first modeled as a two-domain hybrid asymmetric system. An optimization problem is formulated to obtain a stable human-like gait. The proposed controllers are then developed for the combined human/prosthesis model and the optimized reference gait. The stability of all three controllers is proven using the Lyapunov stability theorem, ensuring convergence to the desired gait. The proposed controllers are first verified on a bipedal walking robot as a hybrid human/prosthesis model in simulation. They are then experimentally tested on a treadmill with an able-bodied subject using third iteration of AMBER Prosthetic (AMPRO3), a custom self-contained powered transfemoral prosthesis. Finally, outdoor tests are carried out using AMPRO3 with three test subjects walking on level ground, uphill slopes, and downhill slopes at slope angles of 3° and 8°, to demonstrate walking in different real-world environments.