Developing a Linear Quadratic Regulator for Human Lower Extremity Exoskeleton Robot

During the last two decades, exoskeleton robot-assisted neurorehabilitation has received a lot of attention. The major reason for active research in rehabilitation is its ability to provide various types physical therapy at different stages and neurological recovery. performance greatly influenced by robot motion control system. Robot dynamics are nonlinear, but many linear schemes can adequately handle nonlinear with help feedback linearization techniques. In this study, dynamic model human lower extremities was developed. A state-space form extremity presented. LuGre friction used simulate joint friction. Linear Quadratic Regulator (LQR) designed dynamics. Dynamic simulations were carried out Matlab-Simulink environment. controller's tracking demonstrated presence developed controller’s assessed comparing results obtained using LQR other controllers (PID, Computed torque control, Sliding mode control). For verification, same dynamics, model, trajectories used. stability system also analyzed.