Authors
Jacob Goodman, Jinho Kim, Andrew S. Lee, S. Andrew Gadsden, Mohammad Al-Shabi
Corresponding Author
Jacob Goodman
Available Online 1 September 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.2.8
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.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).