Journal of Robotics, Networking and Artificial Life

Volume 4, Issue 2, August 2017, Pages 142 - 145

A Variable Structure-Based Estimation Strategy Applied to an RRR Robot System

Authors
Jacob Goodman, Jinho Kim, Andrew S. Lee, S. Andrew Gadsden, Mohammad Al-Shabi
Corresponding Author
Jacob Goodman
Available Online 1 August 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.2.8How to use a DOI?
Keywords
Robotic manipulator, estimation theory, Kalman filter, smooth variable structure filter.
Abstract
Nonlinear estimation strategies are important for accurate and reliable control of robotic manipulators. This brief paper studies the application of estimation theory to a simple robotic manipulator. Two estimation techniques are considered: the classic extended Kalman filter (EKF), and the robust smooth variable structure filter (SVSF). The EKF is included to present a basic background in estimation techniques and the SVSF is described and implemented on the system. We simulate the SVSF applied to a dynamically modeled three-link robotic manipulator. The results of the paper demonstrate that nonlinear estimation techniques such as the SVSF can be applied effectively to robots with modeling uncertainty and external disturbances.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
4 - 2
Pages
142 - 145
Publication Date
2017/08
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2017.4.2.8How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Jacob Goodman
AU  - Jinho Kim
AU  - Andrew S. Lee
AU  - S. Andrew Gadsden
AU  - Mohammad Al-Shabi
PY  - 2017
DA  - 2017/08
TI  - A Variable Structure-Based Estimation Strategy Applied to an RRR Robot System
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 142
EP  - 145
VL  - 4
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2017.4.2.8
DO  - https://doi.org/10.2991/jrnal.2017.4.2.8
ID  - Goodman2017
ER  -