By Topic

Multiple model-based control of robotic manipulators: theory and experimentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Leahy, M.B., Jr. ; Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA ; Sablan, S.J.

The multiple-model-based control (MMBC) technique utilizes knowledge of nominal robot dynamics and principles of Bayesian estimation to provide payload-independent trajectory tracking accuracy. The MMBC algorithm is formed by augmenting a model-based controller with a form of multiple-model adaptive estimation (MMAE). The MMAE uses perturbation models of the robot dynamics and joint angle measurements to provide an estimate of the payload parameters required to minimize trajectory tracking errors. The model-based controller combines the a priori knowledge of robot structure with the payload estimate to produce the multiple models of the manipulator dynamics required to maintain controller accuracy. The development of the PUMA-specific version of the MMBC is presented first three links of PUMA-560, along with experimental validation of extensive simulation studies

Published in:

Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on

Date of Conference:

5-7 Sep 1990