A Variable Structure-Based Estimation Strategy Applied to an RRR Robot System
- https://doi.org/10.2991/jrnal.2017.4.2.8How to use a DOI?
- Robotic manipulator, estimation theory, Kalman filter, smooth variable structure filter.
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.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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 - 2017/09/01 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 -