RBF Neural Network based Trajectory Control and Impedance Control of a Upper Limb Tele-rehabilitation Process

Ting Wang, Yanfeng Pu

Abstract

In the passive tele-rehabilitation process, the safety is the most important thing for patients avoiding the secondary damage of the impaired upper limb. Aiming at adjusting the appropriated contact force in time during the training exercises, an adaptive impedance control is proposed for the slave side. At the same time, the trajectory control based on the Hamilton-Jacobi-Inequality theory and the RBF Neural network is performed for the master manipulator operated by therapists. The stability is analyzed and numerical simulations show the efficiencies and high performances of the proposed method.

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