This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Web of Science (2) Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Austin, D. J. Articles by McCarragher, B. J. Search for Related Content Social Bookmarking                         What's this?

Model-Adaptive Hybrid Dynamic Control for Robotic Assembly Tasks

Center for Autonomous Systems, Royal Institute of Technology, SE 100-44 Stockholm, Swedend.austin{at}computer.org

Brenan J. McCarragher

Department of Engineering, Faculties, Australian National University, Canberra, ACT 0200, Australiabrenan{at}faceng.anu.edu.au

A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.

Key Words: hybrid dynamic system • adaptive control • constrained motion

The International Journal of Robotics Research, Vol. 18, No. 10, 998-1012 (1999)
DOI: 10.1177/02783649922067672


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?