Journal of Robotics, Networking and Artificial Life

Volume 4, Issue 2, September 2017, Pages 146 - 149

Weighted Multiple Model Adaptive Control for a Category of Systems with Colored Noise

Authors
Yuzhen Zhang, Weicun Zhang, Qing Li
Corresponding Author
Yuzhen Zhang
Available Online 1 September 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.2.9How to use a DOI?
Keywords
discrete-time; colored noise; multiple model adaptive control; stability; convergence.
Abstract
The multiple model adaptive control (MMAC) of discrete-time stochastic system with colored noise is considered in this paper. Model set contains one adaptive identification and some fixed models. Based on the output errors of the models, a simple weighting algorithm is adopted with guaranteed convergence. The proofs of the stability and convergence of system are presented. Besides, the influence of initial value of adaptive model on system performance is described. Finally, computer simulation results can verify the theoretical results.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
4 - 2
Pages
146 - 149
Publication Date
2017/09
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2017.4.2.9How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Yuzhen Zhang
AU  - Weicun Zhang
AU  - Qing Li
PY  - 2017
DA  - 2017/09
TI  - Weighted Multiple Model Adaptive Control for a Category of Systems with Colored Noise
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 146
EP  - 149
VL  - 4
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2017.4.2.9
DO  - https://doi.org/10.2991/jrnal.2017.4.2.9
ID  - Zhang2017
ER  -