Remodeling for fuzzy PID controller based on neural networks

被引：0
|
作者：
Li, Taifu [1 ]
Su, Yingying [2 ]
Zhong, Bingxiang [1 ]
机构：
[1] Chongqing Univ Sci & Technol, Dept Elect Informat Engn, Chongqing 400050, Peoples R China
[2] Chongqing Inst Technol, Dept Elect Informat & Automat, Chongqing 400050, Peoples R China
来源：
FUZZY INFORMATION AND ENGINEERING, PROCEEDINGS | 2007年 / 40卷
关键词：
fuzzy PID; neural network; function approximation; remodeling; MATLAB;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Aimed at implementation puzzles of fuzzy PID controller because of computational complexity, in this paper, in order to reduce computational complexity and realize real-time control, authors utilized universal approximation of the NN to reconstruct an equivalent NN model to accurately approximate a known fuzzy PID controller. Consequently, authors simulated to control the same process model by the fuzzy PID controller and the remodeling NN with different reference inputs, respectively. Results show that control qualities from two different controllers were extremely similar. Therefore, the fuzzy PID controller can be replaced by a remodeling NN in purpose of reducing the computational complexity, dimensional disaster and improving the real-time performance.
引用
收藏
页码：714 / +
页数：2
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