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Neural Network Control of an Optimized Regenerative Motor Drive for a Lower-limb Prosthesis

    • Cleveland State University

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A voltage source converter (VSC) is incorporated in an active prosthetic leg design. The VSC supplies power to the prosthesis motor and regenerates energy from the prosthesis motor for storage in a supercapacitor bank. An artificial neural network controls the VSC switching so that the prosthesis motor generates a knee torque that matches the torque that is output from a passivity-based controller (PBC). The neural network, PBC, and prosthesis motor parameters are optimized with an evolutionary algorithm to achieve knee angle tracking. Several reference trajectories from able-bodied walking were tracked with an RMS tracking error of less than 0.5° while regenerating up to 67 Joules of energy during four gait cycles.

    Original languageAmerican English
    JournalAmerican Control Conference (ACC)
    DOIs
    StatePublished - Jan 1 2017

    Disciplines

    • Biomechanical Engineering
    • Electrical and Computer Engineering

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