Journal of Robotics, Networking and Artificial Life

Volume 2, Issue 2, September 2015, Pages 69 - 72

Adaptive Multiple-Model Control of A Class of Nonlinear Systems

Authors
Chao Yang, Yingmin Jia
Corresponding Author
Chao Yang
Available Online 1 September 2015.
DOI
https://doi.org/10.2991/jrnal.2015.2.2.1How to use a DOI?
Keywords
adaptive control, multiple-model design, nonlinear systems, asymptotic tracking
Abstract

In this paper, an adaptive multiple-model controller is developed for nonlinear systems in parametric-strict-feedback form. Unlike the previous results, a switching scheme is not required here to switch the most appropriate model into the controller design. The new scheme reduces the number of identification models and uses information provided by all the models more efficiently than previous results by using the convex combination of estimates of parameters. The method guarantees parameter convergence and global asymptotic stability of the closed-loop system. The global boundness of closed-loop signals and asymptotic convergence to zero of tracking error are proved. A simulation example is included to demonstrate the effectiveness of the obtained results.

Copyright
© 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/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
2 - 2
Pages
69 - 72
Publication Date
2015/09/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2015.2.2.1How to use a DOI?
Copyright
© 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  - Chao Yang
AU  - Yingmin Jia
PY  - 2015
DA  - 2015/09/01
TI  - Adaptive Multiple-Model Control of A Class of Nonlinear Systems
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 69
EP  - 72
VL  - 2
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2015.2.2.1
DO  - https://doi.org/10.2991/jrnal.2015.2.2.1
ID  - Yang2015
ER  -