Research on Trajectory Tracking of Lower Limb Exoskeleton Rehabilitation Robot Based on Sliding Mode Control

Abstract

The patient number of lower limb motor dysfunction, such as stroke and spinal cord injury, was increasing every year. For the early rehabilitation, repeated high-intensity exercise was very important for the recovery of limb motor function and the reduction of amyotrophy. Therefore, this paper was proposed a lower limb exoskeleton robots (LERs) for rehabilitation training. Based on the input-output stability theory, we established the mathematical model of sliding mode controller (SMC) and built the control hardware system. From the simulation, we found the tracking error of SMC was smaller and the response was faster than PD controller. So it was proved that SMC was more suitable for exoskeleton trajectory tracking than classical PD controller. According to the simulation and walking experiments, the chattering of SMC was decreased by using the saturation function as the switching function. Therefore, the reaching law of the gait trajectory tracking error would approach to zero at different rates inside and outside of the boundary layer (ẟ), and thus the SMC could be adaptive. The simulation and experiments results indicate that SMC was a suitable choice for controlling a physical exoskeleton robot.