Modeling and Control Analysis of Horizontal Cable-Driven Rehabilitation Robot

Addressing the current problem that the lower limbs of patients in the early stages of rehabilitation affect the effect of rehabilitation training due to muscle weakness, this paper proposes a modeling and control strategy for the new horizontal cable-driven rehabilitation robot (HCDRR). Firstly, the kinematic model of lower limb is established to derive the mapping relationship between the joint angle and the trajectory of the moving platform. The relationship between the change of cable length and the trajectory of the ankle joint of the lower limb is derived by the spatially closed vector method. Secondly, the dual-space dynamics model about the human lower limb workspace and the cable space is established, and the cable tension is optimized to ensure that the cable is always under tension. Finally, a dual-space adaptive neural network sliding mode control strategy is proposed to address the problems of modeling errors and uncertain disturbances in horizontal cable-driven rehabilitation systems. Taking the rehabilitation action of hip and knee flexion as an example for experimental verification, the results show that the proposed control algorithm can achieve high-precision trajectory tracking.