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

DOI

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.

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  - Yuzhen Zhang
AU  - Weicun Zhang
AU  - Qing Li
PY  - 2017
DA  - 2017/09/01
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  - 10.2991/jrnal.2017.4.2.9
ID  - Zhang2017
ER  -