Nonlinear iterative learning control of 5 DOF upper-limb rehabilitation robot

This paper focus on the nonlinear and uncertainty problems in the upper limb rehabilitation robot trajectory tracking control. Considering that the rehabilitation robot system need to be performed a repetitive task and the properties of iterative learning control, we introduce a class of nonlinear saturation function and put forward a nonlinear iterative learning control algorithm. This algorithm improved the commonly used linear PID robot dynamics control. It gained the good control quality under the condition of the model information is not accurate and only the position feedback can be measured. It realized the asymptotic stability tracking of the periodic reference input. Combined with rehabilitation robot dynamics model characteristics, applying Lyapunov stability theory to prove the global asymptotic stability of the closed-loop system. The simulation results of five degrees of freedom of rehabilitation robot system show that the proposed nonlinear iterative learning control has good control performance.