Min Max control of nonlinear systems using Universal Learning Networks

Hongping Chen, Kotaro Hirasawa, Jinglu Hu, Junichi Murata

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

A Min Max robust control method is proposed for nonlinear systems based on the use of the higher order derivatives calculation of Universal Learning Networks (ULNs). An extended criterion function containing sensitivity terms is considered for controller design and the criterion function is evaluated at several specific operating points corresponding to certain system parameters. The ULNs learning is then performed in such a way that, at each step, it minimizes the worst criterion function among several operating points. It is found that the proposed control method is less time-consuming in the ULNs learning and a obtained controller has better performance than the conventional methods.

Original languageEnglish
Pages242-247
Number of pages6
DOIs
Publication statusPublished - 2000
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
Duration: 2000 Jul 242000 Jul 27

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy
Period00/7/2400/7/27

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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