An Adaptive Iterative Learning Based Impedance Control for Robot-Aided Upper-Limb Passive Rehabilitation

In this paper, an anthropomorphic arm is introduced and used to the upper-limb passive rehabilitation therapy. The anthropomorphic arm is constructed via pneumatic artificial muscles so that it may assist patients suffering upper-limb diseases to achieve mild therapeutic exercises. Due to the uncertain dynamic environment, external disturbances and model uncertainties, a combined control is proposed to stabilize and to enhance the adaptivity of the system. In the combined control, an iterative learning control is used to realize accurate position tracking. Meanwhile, an adaptive iterative learning based impedance control is proposed to execute the appropriate contact force during the therapy of the upper-limb. The advantage of the combined control is that it doesn't depend on the accurate model of systems and it may deal with highly nonlinear system which has strong coupling and redundancies. The convergence of the proposed control is analyzed in detail. Numerical simulations are performed to verify the proposed control method. In addition, real experiments are executed on the Southwest anthropomorphic arm.