Research and application of fuzzy control with multiple weighted factors by genetic algorithm
Authors
L.J. Dong
Corresponding Author
L.J. Dong
Available Online April 2015.
- 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/).
Cite this article
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 -