Fuzzy Control and its Applications in QCM Sensor System

DOI

10.2991/jimet-15.2015.130How to use a DOI?

Keywords

Fuzzy Control; Neural Networks; Pattern Recognition; Numerical Analysis

Abstract

Research in the field of neural networks has made significant progress, that progress has attracted a lot of attention and support of the people more money on. Now more and more academic and commercial research is carried out on neural networks, such as chip-based neural networks are developed and applied, and produces a number of complex issues, and treats these problems solved. Obviously, now just a transition period of neural networks. Neural network results from the ability of complex data extraction can be used to extract or detect those patterns for humans or other computer technology is too complex hard to notice a trend. A class of design problems H fuzzy neural network controller. By using Lyapunov-Krasovskii functional theory and judgment theorem to derive a stable process introduces several additional matrices, got some time delay depends on the H progressive. Finally, a numerical example is given to demonstrate the effectiveness and feasibility of the simulation we give H controller.

Copyright

© 2015, 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  - CONF
AU  - Chen Hai Xia
PY  - 2015/12
DA  - 2015/12
TI  - Fuzzy Control and its Applications in QCM Sensor System
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 699
EP  - 702
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.130
DO  - 10.2991/jimet-15.2015.130
ID  - HaiXia2015/12
ER  -