Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)

Novel Methods Ofof Nodes Management Inin Wireless Sensor Networks Byby Predictive Control Model

Authors
Qing Tan
Corresponding Author
Qing Tan
Available Online September 2016.
DOI
10.2991/meici-16.2016.203How to use a DOI?
Keywords
Nodes management; Wireless sensor network; Predictive control model; Control strategy; Parametric model
Abstract

This paper analyzes the main model contents of predictive control. Wireless sensor networks consist of large number of sensor nodes through the network. Predictive control is the three basic characteristics introduced above: predictive model, receding horizon optimization and feedback correction. These methods are belonging to the non parametric model predictive control. The paper puts forward novel methods of nodes management in wireless sensor networks by predictive control model. Experimental results show the effectiveness of the proposed method.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
Series
Advances in Intelligent Systems Research
Publication Date
September 2016
ISBN
10.2991/meici-16.2016.203
ISSN
1951-6851
DOI
10.2991/meici-16.2016.203How to use a DOI?
Copyright
© 2016, 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  - CONF
AU  - Qing Tan
PY  - 2016/09
DA  - 2016/09
TI  - Novel Methods Ofof Nodes Management Inin Wireless Sensor Networks Byby Predictive Control Model
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 978
EP  - 983
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.203
DO  - 10.2991/meici-16.2016.203
ID  - Tan2016/09
ER  -