An Adaptive Low-Dimensional Control for a Hybrid Neuroprosthesis

Abstract Hybrid neuroprostheses that use both electric motor drives and functional electrical stimulation for the restoration of walking in persons with paraplegia have a promising potential. However, the hybrid actuation structure introduces effector redundancy, making the system complex and difficult to control. In this paper we design a low-dimensional controller inspired from the muscle synergy principle. The new controller requires few control signals to actuate multiple effectors in a hybrid neuroprostheses. The development of the controller and a Lyapunov stability analysis, which yielded semi-global uniformly ultimately boundedness is presented in this paper. Computer simulations were performed to test the new controller on a 2 degree of freedom fixed hip model.

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