Improving the motion performance for an intelligent walking support machine by RLS algorithm

Yina Wang*, Shuoyu Wang, Renpeng Tan, Yinlai Jiang, Kenji Ishida, Yo Kobayashi, Masakatsu G. Fujie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


To make the old people and handicapped people move easily by themselves, an omni-directional walking support machine (WSM) has been developed. In our previous study, to improve the motion performance of the WSM, a digital acceleration control method has been developed to deal with the nonlinear friction. However, the design of the digital acceleration controller requires to know the exact plant parameters of the WSM which are variable due to center of gravity (COG) shift and load changes. The change of the plant parameters affects the motion performance of the digital acceleration control system. Therefore, in this paper, a discrete-time system identification method using recursive least squares (RLS) algorithm is proposed to online identify the WSM's plant parameters for the digital acceleration controller. Simulations are executed and compared with the digital acceleration controller without using RLS algorithm, and the results demonstrate the feasibility and effectiveness of the proposed control method.

Original languageEnglish
Pages (from-to)1177-1182
Number of pages6
JournalICIC Express Letters
Issue number4
Publication statusPublished - 2013


  • Digital acceleration control
  • Online identification
  • Recursive least squares
  • Walking support machine

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering


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