Intelligent sliding mode control for robots systems with model uncertainties

Sung Jin Yoo, Yoon Ho Choi, Jin Bae Park

Research output: Contribution to journalArticlepeer-review


This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1014-1021
Number of pages8
JournalJournal of Institute of Control, Robotics and Systems
Issue number10
Publication statusPublished - 2008 Oct

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Applied Mathematics


Dive into the research topics of 'Intelligent sliding mode control for robots systems with model uncertainties'. Together they form a unique fingerprint.

Cite this