Adaptive Control of Man-machine Interaction Force for Lower Limb Exoskeleton Rehabilitation Robot

Aiming at the passive rehabilitation training based on standard gait trajectory can not meet the training needs of lower limb paralyzed patients, a strategy for the lower limb rehabilitation robot interactive force adaptive controlling is proposed, and the adaptive sliding mode control method based on RBF neural network that can realize the rehabilitation training is designed. In order to better meet the needs of the wearer's rehabilitation training, this method takes the walking gait of healthy humans for the position control of the lower extremity exoskeleton, and the leg force of the exoskeleton wearer is used as the force control constraint and the basis for adaptive interaction force adjustment. The experimental results show that this metho ◦ d can effectively adjust the human-machine interaction force in rehabilitation process, and the stability and following character of the exoskeleton control are better, which can meet the rehabilitation needs of patients with lower limb residual muscle strength.