A novel robust adaptive control algorithm with finite-time online parameter estimation of a humanoid robot arm

Muhammad Nasiruddin Mahyuddin, Said G Khan, Guido Herrmann

Research output: Contribution to journalArticle (Academic Journal)peer-review

29 Citations (Scopus)
424 Downloads (Pure)

Abstract

A novel robust adaptive control algorithm is proposed and implemented in real-time on two degrees-of-freedom (DOF) of the humanoid Bristol-Elumotion-Robotic-Torso II (BERT II) arm in joint-space. In addition to having a significant robustness property for the tracking, the algorithm also features a sliding-mode term based adaptive law that captures directly the parameter estimation error. An auxiliary filtered regression vector and filtered computed torque is introduced. This allows the definition of another auxiliary matrix, a filtered regression matrix, which facilitates the introduction of a sliding mode term into the adaptation law. Parameter error convergence to zero can be guaranteed within finite-time with a Persistent-Excitation (PE) condition or Sufficient Richness condition for the demand. The proposed scheme also exhibits robustness both in the tracking and parameter estimation errors to any bounded additive disturbance. This theoretical result is then exemplified for the BERT II robot arm in simulation and for experiments.
Original languageEnglish
Pages (from-to)294-305
Number of pages12
JournalRobotics and Autonomous Systems
Volume62
Issue number3
Early online date15 Oct 2013
DOIs
Publication statusPublished - Mar 2014

Keywords

  • Adaptive control
  • Robotic arm
  • Parameter estimation

Fingerprint Dive into the research topics of 'A novel robust adaptive control algorithm with finite-time online parameter estimation of a humanoid robot arm'. Together they form a unique fingerprint.

Cite this