Decentralized stabilization of neural network linearly interconnected systems via T-S fuzzy control

被引:4
|
作者
Hsiao, Feng-Hsiag
Liang, Yew-Wen
Xu, Sheng-Dong
Lee, Gwo-Chuan
机构
[1] Natl Taiwan Univ, Dept Elect Engn, Tainan 700, Taiwan
[2] Natl Chiao Tung Univ, Dept Elect & Control Engn, Hsinchu 30010, Taiwan
[3] Natl United Univ, Dept Comp Sci & Informat Engn, Kung Ching Li 360, Miaoli, Taiwan
关键词
D O I
10.1115/1.2234492
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The stabilization problem is considered in this study for a neural-network (NN) linearly interconnected system that consists of a number of NN models. First, a linear difference inclusion (LDI) state-space representation is established for the dynamics of each NN model. Then, based on the LDI state-space representation, a stability criterion in terms of Lyapunovs direct method is derived to guarantee the asymptotic stability of closed-loop NN linearly interconnected systems. Subsequently, according to this criterion and the decentralized control.scheme, a set of Takagi-Sugeno (T-S) fuzzy controllers is synthesized to stabilize the NN linearly interconnected system.. Finally, a numerical example with simulations is given to demonstrate the concepts discussed throughout this paper.
引用
收藏
页码:343 / 351
页数:9
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