Stability analysis of nonlinear systems using high order derivatives of universal learning networks

K. Hirasawa, Y. Yu, J. Hu, Junichi Murata

Research output: Contribution to conferencePaper

Abstract

In this paper, a stability analysis method based on the higher order derivatives of ULNs is proposed. In the proposed method, the following are proposed. Firstly, 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. Secondly, the locally asymptotically stable region, where asymptotical stability is secured approximately is obtained by comparing the first order derivatives and higher order derivatives.

Original languageEnglish
Pages1273-1278
Number of pages6
Publication statusPublished - Jan 1 2001
EventInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States
Duration: Jul 15 2001Jul 19 2001

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'01)
CountryUnited States
CityWashington, DC
Period7/15/017/19/01

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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    Hirasawa, K., Yu, Y., Hu, J., & Murata, J. (2001). Stability analysis of nonlinear systems using high order derivatives of universal learning networks. 1273-1278. Paper presented at International Joint Conference on Neural Networks (IJCNN'01), Washington, DC, United States.