The Application of Learning Impedance Control to Exoskeleton Arm

Abstract:

In this paper, we discuss the application of learning impedance control scheme to exoskeleton arm driven by pneumatic artificial muscles (PAM), for assisting in the rehabilitation of patients who suffer from debilitating illness. An iterative learning impedance control problem for robotic manipulators is analyzed, proposed and solved. The target impedance reference modifies a desired trajectory according to the force signals and position signals of the joint. The desired control input of learning impedance control was estimated by radial basis function (RBF) neural network incorporated experience database. The curves of experiment result on the experimental setup show that the algorithm is successful also in the application of exoskeleton arm.

• Periodical: Advanced Materials Research (Volumes 463-464)
• Pages: 900-904
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.463-464.900
• Online since: February 2012
• Authors: Jie Liu, Yu Wang, He Ting Tong, Ray P.S. Han
• Keywords: Exoskeleton Arm, Learning Impedance Control, Neural Network (NN), Pneumatic Artificial Muscle (PAM)

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