Simulation and analysis of a prosthetic ankle using the tacit learning system control algorithm

Abstract

The objective of this thesis is to apply the Tacit Learning System (TLS) developed by Shimoda et al. to a prosthetic lower limb. The ankle prosthesis is constructed in simulation while three different control schemes, all based on TLS, are applied and analyzed. During this thesis, two experiments are conducted to provide additional data helping with understanding and guiding as input for the simulated prosthesis. From the three control schemes, optimizing the stiffness with TLS indicates have the best and most stable effect on the prosthesis. Therefore, it is concluded that the Tacit Learning System has potential to be applied to an actual ankle prosthesis.