Iterative learning based output feedback control for electro-hydraulic loading system of a gait simulator

In this paper, a novel gait simulator is developed for in vitro studies of the normal kinematics and kinetics of the human foot during the stance phase of the gait. In order to make the ground reaction force of the gait simulation in a manner similar to in vivo, an electro-hydraulic loading system (EHLS) is utilized for tibia loading. Since only the position and loading force signals are available, a high-gain observer is designed to estimate the unmeasured states of the EHLS, and the dynamic surface control is implemented for position tracking of the EHLS. The desired position trajectory of the EHLS could be optimized by an iterative learning mechanism such that the tibia loading force could be as close as possible to the target curve in the complex gait simulation process. The experimental results have verified the effectiveness of the proposed control method, and the average tibia loading error can be maintained within 1.5% of the total loading range.