Disturbance estimation for robotic systems using continuous integral sliding mode observer

Zengjie Zhang, Dirk Wollherr, Homayoun Najjaran

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This article presents a novel force-sensor-less method for the estimation of external forces for a general class of second-order robotic systems. The method is based on the integral sliding mode observer (ISMO) which serves as a second-order differentiator for the position measurement of the system. As a result, the system states and disturbance are estimated without explicitly using force and velocity measurements. To apply the ISMO to the general second-order systems, a proper assumption is proposed to address their nonlinearity and discontinuity. The boundary-layer method is applied to ensure that the virtual inputs of the observer are continuous such that the chattering phenomenon is attenuated. A Lyapunov-based method is used to analyze the influence of the boundary layers on the convergence of the state- and disturbance-estimation errors. This influence, mainly determined by the boundary-layer scalars, is given in analytical forms as a reference for parameter selection. The method is evaluated by numerical simulation on a robot manipulator system and compared with a conventional sliding mode observer (SMO). The validation of the performance of the continuous ISMO indicates its generalizability to general second-order robotic systems. Also, the advantage of continuous ISMO over the conventional SMO is reflected by its small estimation errors and superior responsiveness. In general, the proposed method in this paper may interest those who are seeking solutions for haptic robotic tasks without using force sensors.

Original languageEnglish
Pages (from-to)7946-7966
Number of pages21
JournalInternational Journal of Robust and Nonlinear Control
Volume32
Issue number14
DOIs
StatePublished - 25 Sep 2022

Keywords

  • disturbance observation
  • fault detection and isolation
  • integral sliding mode
  • robotic system
  • sliding mode observer

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