Control of the Robotic Leg Prostheses Based on a Neuromuscular Model

Traditional control method for prostheses is under the target locomotion and the known terrain conditions. The relationship between the torque and angle for each joint can be build from the measurements of normal human walking locomotion. Hence, these methods can not adapt to the different walking locomotion or the terrain variations. This paper presents an adaptive muscle-reflex controller, which utilizes the knee plantar flexor to comprise a Hill-type muscle to control the joint's movement. The parameters for controller were adjusted to fit the human knee's performance based on the Hill-type muscle model. Then, the experiments were conducted for the level ground walking, stair ascent walking and stair descent walking. For these experiments, it was observed that the powered prosthesis based on the neuromuscular controller can automatically adapt to the terrain variations, similarly to the normal human walking locomotion, without the known of the specific terrain variations.