A new robust neural network controller designing method for nonlinear systems

H. Chen, K. Hirasawa, J. Hu, J. Murata

Research output: Contribution to conferencePaper

Abstract

A new designing method of a robust neural network controller against system environment changes using Universal Learning Network (ULN) is considered in this paper. With the introduced method, the worst values of system parameters can be searched as well as the optimization of controller parameters through a dual learning algorithm, which includes maximization and minimization procedures. Therefore, the robust controller can be obtained by minimizing the criterion function regarding the worst values of system parameters. Simulation results demonstrate that the system performance has been improved compared with the conventional method by using the proposed method.

Original languageEnglish
Pages497-502
Number of pages6
Publication statusPublished - 2001 Jan 1
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States
Duration: 2001 Jul 152001 Jul 19

Conference

ConferenceInternational Joint Conference on Neural Networks (IJCNN'01)
CountryUnited States
CityWashington, DC
Period01/7/1501/7/19

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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