Joint Space Control of a Lower Limb Exoskeleton Using ANFIS

This paper presents a novel control approach for a lower limb exoskeleton based on adaptive neuro-fuzzy inference system (ANFIS). An exoskeleton is a wearable robot, usually with an anthropomorphic configuration, capable of tracking the movements of the user’s extremities. The goal is to design a controller such that robot can track the human’s motion without the human feeling an interaction force. A ten Degrees of Freedom lower limbs exoskeleton is considered to study the performance of the proposed controller. The system is actuated by four pneumatic actuators which are located in hip and knee joints. For each actuator, a separate ANFIS is trained, witch control exoskeleton in joint space based on the angles of the knee and hip joints in sagittal plane. The simulation results demonstrate that proposed controller is tracked the human’s motion with minimal error.