Research and application of fuzzy control with multiple weighted factors by genetic algorithm

DOI

10.2991/peee-15.2015.73How to use a DOI?

Keywords

Self-correction fuzzy controller genetic algorithm.

Abstract

It is difficult to control the complex object with lagging uncertainty and nonlinearity effectively. To solve this kind of control problem, this paper presents a self-correction fuzzy controller with multiple weighted factors based on genetic algorithm. According to information achieved on line, it finds the global optimum weighted factors with a high speed by the improved genetic algorithm so that to amend and perfect the control rules. It also has done some simulation experiments in the tobacco-redrying control process. The simulation results demonstrate that this kind of control method can achieve good performance.

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  - L.J. Dong
PY  - 2015/04
DA  - 2015/04
TI  - Research and application of fuzzy control with multiple weighted factors by genetic algorithm
BT  - Proceedings of the 2015 International Conference on Power Electronics and Energy Engineering
PB  - Atlantis Press
SP  - 266
EP  - 269
SN  - 2352-5401
UR  - https://doi.org/10.2991/peee-15.2015.73
DO  - 10.2991/peee-15.2015.73
ID  - Dong2015/04
ER  -