Funnel control based on unknown system dynamics estimator for hydraulically-driven lower limb exoskeleton robot

The hydraulically-driven lower limb exoskeleton robot (HDLLER) can enhance the motion capabilities of human lower limbs. However, due to inherent uncertainties and external human-robot coupling disturbances, it poses significant challenges to precise trajectory tracking control. Therefore, a novel funnel control (FC) strategy based on an unknown system dynamics estimator (USDE) is proposed to compensate for unknown internal and external dynamic influences, thus further improving robot performance. Firstly, the HDLLER high-order dynamic model containing human-robot coupling disturbances is transformed into a Brunovsky canonical form, effectively circumventing the 'explosion of complexity' problem in high order strict feedback systems. Subsequently, a set of high gain observers (HGO) is introduced to reconstruct the states of the transformed system. A modified funnel function is embedded in feedback controller to constrain the tracking error within prescribed boundaries, ensuring satisfactory transient and steady-state performances. Additionally, a simple yet effective USDE is incorporated to compensate for the lumped unknown dynamics. Different comparative simulations and gait experiments have verified the effectiveness of the proposed control method.