Lower Limb Exoskeleton Control via Linear Quadratic Regulator and Disturbance Observer

Achieving a more human-like trajectory of lower limb exoskeleton for locomotion assistance requires accurate trajectory tracking control. However, this task has challenges due to the nonlinearities and disturbances acting on the system, which is interacting with the wearer and the surroundings. In order to improve the control performance, a Linear Quadratic Regulator with integral action (LQRi) and Unknown Input Observer (UIO) to compensate for disturbances are introduced. The chosen control strategy is model-based, therefore an accurate model of the exoskeleton is derived. Experiments are conducted, and the testing results compared with the previous Proportional Derivative (PD) controller show a performance improvement throughout the gait cycle, which proves the proposed control to be effective and easily implementable for lower limb exoskeleton control.