Parameter Design of Disturbance Observer for a Robust Control of Two-Wheeled Wheelchair System

Aiko Dinale, Kazuya Hirata, Matteo Zoppi, Toshiyuki Murakami

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


The wheelchair system presented in this research has only two wheels. This mechanical choice increases the maneuverability of the wheelchair itself, making the system more agile and able to overcome small obstacles (e.g. step, bump, rough terrain, etc.) in different kinds of environments. In addition, the user is able to train her/his body, since it is necessary to lean the body forward and backward to drive the wheelchair along the corresponding direction. Besides these advantages, there is a big drawback: the system is naturally unstable. For this reason, a motion controller is necessary to keep the wheelchair balanced. Furthermore, it is not possible to have a direct control along the pitch direction and a stable configuration is reached only through the actuation of the wheels. In order to estimate the torque acting on the pitch direction, the synthesized pitch angle disturbance observer (SPADO) is introduced. The results collected by SPADO combined with a Lyapunov controller makes the stabilization possible. During the design phase, particular attention should be paid to the inertia parameters variation, otherwise the performance of the entire system decreases. A detailed stability analysis is carried on to identify, from a theoretical point of view, the best parameter tuning. Then, the results from the experiments on the real platform are presented to verify the theoretical results.

Original languageEnglish
Pages (from-to)135-148
Number of pages14
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number1
Publication statusPublished - 2015 Jan


  • Disturbance observer
  • Inertia parameters calibration
  • Inverted pendulum
  • Robust motion control
  • Stability analysis
  • Two-wheeled wheelchair

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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