An Extremum-Seeking Control Approach For Constrained Robotic Motion Tasks
Keywords
Extremum seeking; Model reference adaptive control; Robot control; State tracking
Abstract
In this paper, we propose two adaptive control schemes for multiple-input systems for execution of robot end-effector movements in the presence of parametric system uncertainties. The design of these schemes is based on Model Reference Adaptive Control (MRAC) while the adaptation of the controller parameters is achieved by Extremum Seeking Control (ESC). The two control schemes, which are called Multiple-Input ESC-MRAC and Multiple-Input Adaptive-Dynamic-Inversion ESC-MRAC, are suitable for linear and nonlinear systems respectively. Lyapunov and averaging analysis shows that the proposed schemes achieve practical asymptotic reference state tracking. The proposed methods are evaluated in simulations and in a real-world robotic experiment.
Publication Date
7-1-2016
Publication Title
Control Engineering Practice
Volume
52
Number of Pages
1-14
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.conengprac.2016.04.004
Copyright Status
Unknown
Socpus ID
84963660249 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84963660249
STARS Citation
Koropouli, Vasiliki; Gusrialdi, Azwirman; Hirche, Sandra; and Lee, Dongheui, "An Extremum-Seeking Control Approach For Constrained Robotic Motion Tasks" (2016). Scopus Export 2015-2019. 2237.
https://stars.library.ucf.edu/scopus2015/2237