Abstract
Lower limb dynamic models are useful to investigate the biomechanics of the knee and ankle joints, but
many systems have several limitations which includes simplified forces, non physiologic kinematics and the
complicated interactions between the foot and the ground. Many approaches in control of prosthetic
devices use prediction algorithms to estimate ground reaction forces (GRF), which can degrade the
performance and the efficiency of the devices due to calculation errors. In this study, the variation of the
GRF during different gait cycles was investigated in the design of an adaptive fuzzy controller for a
dynamic model of an active ankle-knee prosthesis, the efficiency of the controller was tested for walking
gait, stair ascent and descent. Real experimental kinematics of the lower limb and GRF measured by forces
platforms were selected as the controller inputs and fuzzy reasoning was used to determine the adequate
torques to actuate the prosthetic device model. The capacity of the active prosthesis and the designed
controller to provide walking, stair ascent and descent cycles was tested by comparing the gait kinematics
to those provided by a healthy subject.
Users
Please
log in to take part in the discussion (add own reviews or comments).