Experimental study of rehabilitation robot system based on hierarchical intelligent control

The rehabilitation of stroke patients has been paid much attention in the world, and it will significantly improve the efficiency by introducing the robot technology into the rehabilitation training. According to the mechanical structure of the robot, the functional requirements and safety requirements of the rehabilitation training are proposed in this paper. So this paper presents a new control strategy of rehabilitation robot based on hierarchical intelligent control, which consists of organization level, coordination level, and execution level controller. The Radical Basis Function (RBF) neural network is used as the organization level controller. The coordination level controller consists of the passive and active logic. The active/passive switching experiments and spasticity experiments are studied. The results prove the effectiveness of the active and passive control strategy.