Adaptive Multiple-Model Control of A Class of Nonlinear Systems

DOI

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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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  - 10.2991/jrnal.2015.2.2.1
ID  - Yang2015
ER  -