DocumentCode
1749242
Title
Stability analysis of nonlinear systems using high order derivatives of universal learning networks
Author
Hirasawa, Kotaro ; Yu, Yunqing ; Hu, Jinglu ; Murata, Junichi
Author_Institution
Dept. of Electr. & Electron. Syst. Eng., Kyushu Univ., Fukuoka, Japan
Volume
2
fYear
2001
fDate
2001
Firstpage
1273
Abstract
In this paper, a stability analysis method based on the higher order derivatives of universal learning networks is proposed. In the proposed method, the following are proposed. First, if the absolute values of the first order derivatives of any nodes with respect to any initial disturbances approach zero at time infinity, then the trajectory is locally asymptotically stable. Next, the locally asymptotically stable region, where asymptotic stability is secured approximately, is obtained by comparing the first order derivatives and higher order derivatives
Keywords
asymptotic stability; control system analysis; learning systems; neural nets; nonlinear systems; asymptotic stability; high order derivatives; nonlinear systems; universal learning networks; Asymptotic stability; Delay effects; Differential equations; H infinity control; Input variables; Lyapunov method; Nonlinear dynamical systems; Nonlinear systems; Stability analysis; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.939544
Filename
939544
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