Adaptive control algorithm with parameter optimization using neural networks for an omni-directional walker

Renpeng Tan, Shuoyu Wang, Yinlai Jiang, Kenji Ishida, Masakatsu Fujie

    Research output: Contribution to journalArticle

    3 Citations (Scopus)

    Abstract

    An omni-directional walker, which is able to realize diverse motion groups, has been developed for walking rehabilitation. In a previous study, to improve the path tracking accuracy, an adaptive control algorithm was developed to deal with the center of gravity shift and the load changes caused by the users. However, the control parameters in the nonlinear adaptive control law were manually adjusted. In this paper, a neural network for automatically adjustment of the adaptive control parameters is proposed. According to the rehabilitation program designed by the physical therapists, we simulate the walker's movement along a linear path. The simulation results verify the effectiveness of the parameter optimization using neural network. ICIC International

    Original languageEnglish
    Pages (from-to)201-207
    Number of pages7
    JournalICIC Express Letters, Part B: Applications
    Volume1
    Issue number2
    Publication statusPublished - 2010 Dec

    Fingerprint

    Neural networks
    Patient rehabilitation
    Gravitation

    Keywords

    • Adaptive control
    • Neural networks
    • Omni-directional walker
    • Parameters optimization

    ASJC Scopus subject areas

    • Computer Science(all)

    Cite this

    Adaptive control algorithm with parameter optimization using neural networks for an omni-directional walker. / Tan, Renpeng; Wang, Shuoyu; Jiang, Yinlai; Ishida, Kenji; Fujie, Masakatsu.

    In: ICIC Express Letters, Part B: Applications, Vol. 1, No. 2, 12.2010, p. 201-207.

    Research output: Contribution to journalArticle

    Tan, Renpeng ; Wang, Shuoyu ; Jiang, Yinlai ; Ishida, Kenji ; Fujie, Masakatsu. / Adaptive control algorithm with parameter optimization using neural networks for an omni-directional walker. In: ICIC Express Letters, Part B: Applications. 2010 ; Vol. 1, No. 2. pp. 201-207.
    @article{659bb4a974264151b5af319165b4908e,
    title = "Adaptive control algorithm with parameter optimization using neural networks for an omni-directional walker",
    abstract = "An omni-directional walker, which is able to realize diverse motion groups, has been developed for walking rehabilitation. In a previous study, to improve the path tracking accuracy, an adaptive control algorithm was developed to deal with the center of gravity shift and the load changes caused by the users. However, the control parameters in the nonlinear adaptive control law were manually adjusted. In this paper, a neural network for automatically adjustment of the adaptive control parameters is proposed. According to the rehabilitation program designed by the physical therapists, we simulate the walker's movement along a linear path. The simulation results verify the effectiveness of the parameter optimization using neural network. ICIC International",
    keywords = "Adaptive control, Neural networks, Omni-directional walker, Parameters optimization",
    author = "Renpeng Tan and Shuoyu Wang and Yinlai Jiang and Kenji Ishida and Masakatsu Fujie",
    year = "2010",
    month = "12",
    language = "English",
    volume = "1",
    pages = "201--207",
    journal = "ICIC Express Letters, Part B: Applications",
    issn = "2185-2766",
    publisher = "ICIC Express Letters Office",
    number = "2",

    }

    TY - JOUR

    T1 - Adaptive control algorithm with parameter optimization using neural networks for an omni-directional walker

    AU - Tan, Renpeng

    AU - Wang, Shuoyu

    AU - Jiang, Yinlai

    AU - Ishida, Kenji

    AU - Fujie, Masakatsu

    PY - 2010/12

    Y1 - 2010/12

    N2 - An omni-directional walker, which is able to realize diverse motion groups, has been developed for walking rehabilitation. In a previous study, to improve the path tracking accuracy, an adaptive control algorithm was developed to deal with the center of gravity shift and the load changes caused by the users. However, the control parameters in the nonlinear adaptive control law were manually adjusted. In this paper, a neural network for automatically adjustment of the adaptive control parameters is proposed. According to the rehabilitation program designed by the physical therapists, we simulate the walker's movement along a linear path. The simulation results verify the effectiveness of the parameter optimization using neural network. ICIC International

    AB - An omni-directional walker, which is able to realize diverse motion groups, has been developed for walking rehabilitation. In a previous study, to improve the path tracking accuracy, an adaptive control algorithm was developed to deal with the center of gravity shift and the load changes caused by the users. However, the control parameters in the nonlinear adaptive control law were manually adjusted. In this paper, a neural network for automatically adjustment of the adaptive control parameters is proposed. According to the rehabilitation program designed by the physical therapists, we simulate the walker's movement along a linear path. The simulation results verify the effectiveness of the parameter optimization using neural network. ICIC International

    KW - Adaptive control

    KW - Neural networks

    KW - Omni-directional walker

    KW - Parameters optimization

    UR - http://www.scopus.com/inward/record.url?scp=78650233170&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=78650233170&partnerID=8YFLogxK

    M3 - Article

    AN - SCOPUS:78650233170

    VL - 1

    SP - 201

    EP - 207

    JO - ICIC Express Letters, Part B: Applications

    JF - ICIC Express Letters, Part B: Applications

    SN - 2185-2766

    IS - 2

    ER -